{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Reply Tool - Workflow Engagement Metrics\n",
"**Last Update: 5 January 2020**\n",
"\n",
"[Task](https://phabricator.wikimedia.org/T247139)\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Table of Contents\n",
"\n",
"1. [Are people publishing the replies they start?](#1.-Are-people-publishing-the-replies-they-start?)\n",
"2. [Are people satisfied with the feature?](#2.-Are-people-satisfied-with-the-feature?)\n",
"3. [Are people posting disruptive comments?](#3.-Are-people-posting-disruptive-comments?)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Overview\n",
"\n",
"The [Editing team](https://www.mediawiki.org/wiki/Editing_team) deployed the reply tool as an opt-out preference on Arabic (arwiki), Czech (cswiki) and Hungarian (huwiki) Wikipedias on 24 September 2020. Further information about the Editing team's work on the tool including the design, deployment process, and status updates is available on the [project page](https://www.mediawiki.org/wiki/Talk_pages_project/replying). The purpose of this task is to analyze how people are engaging with the new Replying tool to help answer these questions:\n",
"\n",
"* Are people are having success using the feature?\n",
"* Are people using the tool in ways that negatively impact the experience of others?\n",
"\n",
"Results of this analysis will be used to determine what - if any - changes should be made to the workflow before deploying the feature to more people and beginning and A/B test to determine its impact.\n",
"\n",
"For this analysis, we reviewed eventlogging data from 24 September 2020 (date of deployment an an opt-out preference) through 08 December 2020. For each metric below, we provided a breakdown by wiki where deployed as opt-out and the users' experience level based on cumulative edits."
]
},
{
"cell_type": "code",
"execution_count": 515,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"library(IRdisplay)\n",
"\n",
"display_html(\n",
"'\n",
" '\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"shhh <- function(expr) suppressPackageStartupMessages(suppressWarnings(suppressMessages(expr)))\n",
"shhh({\n",
" library(magrittr); library(zeallot); library(glue); library(tidyverse); library(zoo); library(lubridate)\n",
" library(scales)\n",
"})"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 1. Are people publishing the replies they start?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## **Reply Tool Funnel** :\n",
"\n",
"We reviewed a sample of data from [EditAttemptStep](https://meta.wikimedia.org/wiki/Schema:EditAttemptStep) to determine the percent of users that successfully met each step of the reply tool workflow. Specifically, we reviewed the following:\n",
"* Of the people who click a [ reply ] link (action = 'init'), what % of people see the interface ready (action = 'ready')?\n",
"* Of the people who see the interface is ready action = 'ready, what % of people start typing a comment (action = 'firstChange')?\n",
"* Of the people who start typing a comment (action = 'firstChange'), what % of people click the Reply button (action = 'saveIntent')?\n",
"* Of the people who click the Reply button (action = 'saveIntent'), what % of people successfully publish the comment they were drafting (action = 'saveSuccess')?\n",
"\n",
"The data below reflects the number of users not sessions. These are counts of the percentage of unique people who, at some point during the reviewed timeframe between 24 September 2020 and 08 December 2020, that reached a step (e.g. init, ready, firstchange, etc.) in the Reply Tool comment funnel. Anonymous users were excluded from the analysis as we do not track distinct anonymous users.\n",
"\n",
"The worflow funnel charts below reflects the percent of all reply tool users that clicked a reply link (reached `init`) and completed each step to save their comment. The chart is divided to show the workflow funnel for each user experience level based on the number of cumulative edits. \n"
]
},
{
"cell_type": "code",
"execution_count": 263,
"metadata": {},
"outputs": [],
"source": [
"# collect data on reply tool users workflow completion steps\n",
"query <- \n",
"\"\n",
"--only include full sessions where an init was also logged during the timeframe \n",
" \n",
"WITH init_sessions AS (\n",
"SELECT \n",
" event.editing_session_id AS session_id,\n",
" wiki AS wiki\n",
"FROM event_sanitized.editattemptstep\n",
"WHERE\n",
" event.action = 'init'\n",
" AND year = 2020\n",
" AND dt between '2020-09-24' AND '2020-12-08'\n",
"-- review wikis where deployed as opt-out\n",
" AND wiki IN ('arwiki', 'cswiki', 'huwiki')\n",
" AND event.integration= 'discussiontools'\n",
"-- remove anonymous users\n",
" AND event.user_id != 0\n",
")\n",
"-- review steps completed by each user\n",
"SELECT\n",
"user,\n",
"wiki,\n",
"min(edit_count) AS edit_count,\n",
"-- select first editing interface show to user\n",
"min(editor_interface) AS editor_interface,\n",
"sum(cast(action = 'init' as int)) >= 1 AS init_completed,\n",
"sum(cast(action = 'ready' as int)) >= 1 AS ready_completed,\n",
"sum(cast(action = 'firstChange' as int)) >= 1 AS firstChange_completed,\n",
"sum(cast(action = 'saveIntent' as int)) >= 1 AS saveIntent_completed,\n",
"sum(cast(action = 'saveSuccess' as int)) >= 1 AS saveSuccess_completed\n",
"FROM (\n",
"SELECT\n",
" eas.event.user_editcount AS edit_count,\n",
" eas.event.user_id AS user,\n",
" eas.event.editing_session_id AS session_id,\n",
" eas.event.editor_interface AS editor_interface,\n",
" eas.event.action AS action,\n",
" eas.wiki AS wiki,\n",
" COUNT(*) AS events\n",
"FROM event_sanitized.editattemptstep eas\n",
"INNER JOIN\n",
" init_sessions \n",
" ON eas.event.editing_session_id = init_sessions.session_id \n",
" AND eas.wiki = init_sessions.wiki\n",
"WHERE\n",
" year = 2020 \n",
"-- events since deployment date through 08 December 2020\n",
" AND dt between '2020-09-24' AND '2020-12-08'\n",
"-- review wikis where deployed as opt-out\n",
" AND eas.wiki IN ('arwiki', 'cswiki', 'huwiki')\n",
" AND eas.event.integration= 'discussiontools'\n",
"-- remove anonymous users\n",
" AND eas.event.user_id != 0\n",
"GROUP BY \n",
" eas.event.user_id,\n",
" eas.event.user_editcount,\n",
" eas.event.action,\n",
" eas.event.editor_interface,\n",
" eas.event.editing_session_id,\n",
" eas.wiki\n",
") AS sessions_data\n",
"GROUP BY\n",
"user,\n",
"wiki\n",
"\"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"collect_reply_workflow_steps <- wmfdata::query_hive(query)"
]
},
{
"cell_type": "code",
"execution_count": 265,
"metadata": {},
"outputs": [],
"source": [
"# add column with user edit count buckets and by experience level\n",
"\n",
"reply_workflow_with_editcount <- collect_reply_workflow_steps %>%\n",
" mutate(edit_count_bucket = case_when(\n",
" edit_count == 0 ~ '0 edits',\n",
" edit_count >=1 & edit_count <= 4 ~ '1-4 edits',\n",
" edit_count >=5 & edit_count <= 99 ~ '5-99 edits',\n",
" edit_count >=100 & edit_count <= 999 ~ '100-999 edits',\n",
" edit_count >=1000 ~ '1000+ edits'),\n",
" experience_level = case_when( \n",
" edit_count < 100 ~ 'junior contributors (< 100 cumulative edits)',\n",
" edit_count > 500 ~ 'senior contributors (> 500 cumulative edits)'))\n"
]
},
{
"cell_type": "code",
"execution_count": 266,
"metadata": {},
"outputs": [],
"source": [
"# Order edit counts\n",
"reply_workflow_with_editcount$edit_count_bucket %<>% \n",
" factor(levels= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\"))"
]
},
{
"cell_type": "code",
"execution_count": 267,
"metadata": {},
"outputs": [],
"source": [
"reply_users_workflow_funnel <- reply_workflow_with_editcount %>%\n",
" group_by(wiki, edit_count_bucket, experience_level, editor_interface) %>%\n",
" summarise(init = sum(init_completed == 'true'),\n",
" ready = sum(ready_completed == 'true'),\n",
" firstchange = sum(firstchange_completed == 'true'),\n",
" saveintent = sum(saveintent_completed == 'true'),\n",
" savesuccess = sum(savesuccess_completed == 'true'), .groups = 'drop')\n"
]
},
{
"cell_type": "code",
"execution_count": 268,
"metadata": {},
"outputs": [],
"source": [
"# reorganize data so it can be easily charted \n",
"reply_users_workflow_funnel_clean <- reply_users_workflow_funnel %>%\n",
" gather(\"step\", \"n_users\", 5:9) \n"
]
},
{
"cell_type": "code",
"execution_count": 269,
"metadata": {},
"outputs": [],
"source": [
"# order edit steps to correspond with the steps of the workflow\n",
"reply_users_workflow_funnel_clean$step %<>% \n",
" factor(levels= c(\"init\",\"ready\", \"firstchange\", \"saveintent\", \"savesuccess\"))\n"
]
},
{
"cell_type": "code",
"execution_count": 270,
"metadata": {},
"outputs": [],
"source": [
"# Find total init sessions by edit count bucket across all three target wikis for both interfaces\n",
"init_users_overall <- reply_users_workflow_funnel_clean %>%\n",
" group_by(edit_count_bucket) %>%\n",
" filter(step == 'init') %>%\n",
" summarise(init_users_overall = sum(n_users), .groups = 'drop')\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 271,
"metadata": {},
"outputs": [],
"source": [
"# Find total init sessions across all three target wikis by edit count bucket and editor_interface\n",
"\n",
"init_users_byeditcount <- reply_users_workflow_funnel_clean %>%\n",
" group_by(edit_count_bucket, editor_interface) %>%\n",
" filter(step == 'init') %>%\n",
" summarise(init_users_byeditcount = sum(n_users), .groups = 'drop')\n",
" \n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join with workflow table\n",
"reply_users_workflow_funnel_forplot_overall <- inner_join(reply_users_workflow_funnel_clean, init_users_overall)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join with workflow table\n",
"reply_users_workflow_funnel_forplot_editcount <- inner_join(reply_users_workflow_funnel_clean, init_users_byeditcount)"
]
},
{
"cell_type": "code",
"execution_count": 274,
"metadata": {},
"outputs": [],
"source": [
"# Find total init sessions across all three target wikis by editor experience\n",
"\n",
"init_users_byexperience <- reply_users_workflow_funnel_clean %>%\n",
" group_by(experience_level, editor_interface) %>%\n",
" filter(step == 'init',\n",
" experience_level != 'NA' ) %>% # remove contributors not bucketed into senior or junior levels\n",
" summarise(init_users_byexperience = sum(n_users), .groups = 'drop')\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join with workflow table\n",
"reply_users_workflow_funnel_forplot_experience <- inner_join(reply_users_workflow_funnel_clean, init_users_byexperience)"
]
},
{
"cell_type": "code",
"execution_count": 276,
"metadata": {},
"outputs": [],
"source": [
"# Find total init sessions across all three target wikis by editor experience for both interfaces\n",
"\n",
"init_users_byexperience_both_interfaces <- reply_users_workflow_funnel_clean %>%\n",
" group_by(experience_level) %>%\n",
" filter(step == 'init',\n",
" experience_level != 'NA' ) %>% # remove contributors not bucketed into senior or junior levels\n",
" summarise(init_users_byexperience_both = sum(n_users), .groups = 'drop')\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join with workflow table\n",
"reply_users_workflow_funnel_forplot_experience_both <- inner_join(reply_users_workflow_funnel_clean, init_users_byexperience_both_interfaces)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Workflow funnel across all three opt-out wikis by user's experience level"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Comments made with VisualEditor"
]
},
{
"cell_type": "code",
"execution_count": 465,
"metadata": {},
"outputs": [
{
"data": {
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4RkZGbm7uyZMnY2NjXVxcrDfT6/W+vr6+vr5X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\nMH/+fLmH+p4//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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow across all three target wikis on VE broken down by edit bucket\n",
"\n",
"options(repr.plot.width = 15, repr.plot.height = 10)\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_editcount %>%\n",
" filter(editor_interface == 'visualeditor') %>%\n",
" group_by(step, edit_count_bucket, editor_interface) %>%\n",
" summarise(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_byeditcount, .groups = 'drop') %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.05, lab=c(\"total users: 14\",\"total users: 77\",\"total users: 80\", \"total users: 32\", \"total users: 40\"),\n",
" edit_count_bucket= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\" )), vjust=1) +\n",
" facet_grid(~edit_count_bucket) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Visual Editor Reply Tool Workflow Funnel by Editor Experience \\n Across All Opt-out Wikis\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/ve_reply_workflow_overall_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 283,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow across all three target wikis on VE broken down by junior and senior contributors\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_experience %>%\n",
" filter(editor_interface == 'visualeditor') %>%\n",
" group_by(step, experience_level, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_byexperience) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.05, lab=c(\"total users: 147\",\"total users: 50\"),\n",
" experience_level= c(\"junior contributors (< 100 cumulative edits)\", \"senior contributors (> 500 cumulative edits)\")), vjust=1) +\n",
" facet_grid(~experience_level) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Visual Editor Reply Tool Workflow Funnel for Junior and Senior Contributors \\n Across All Opt-out Wikis\"\n",
" ) +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position = \"none\")\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/ve_reply_workflow_overall_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Across all three opt-out wikis, there is only a slight drop in the number of senior contributors that complete each step of the reply workflow using visual editor with 84% of all senior contributors sucessfully completing their edit. The largest decrease occurs between `init` and `ready` which may be due to network disruptions during the visual editor load time.\n",
"\n",
"For junior contributors, the biggest drop in number of contributors occurs between `ready` (the contributor clicks the reply link and the editing interface is ready) and `firstchange` (the user begins typing a comment). However, the rate of drop-off decreases after this step. While only 79% percent of junior contributors that successfully loaded the editing interface started typing a comment, 93% percent of junior contributors that started typing a comment were able to successuly save their comment. \n",
"\n",
"Interestingly, reply tool users with 5 to 99 cumulative had the highest drop-off between `firstchange` and `saveintent` steps."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Comments made with Wikitext"
]
},
{
"cell_type": "code",
"execution_count": 466,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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w888MAtt9zyla98pVOnTp9vpkegxvmbk37890F/Q9lA6nqXa/Y2b9480v9q0iI9BeGb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\nXmjfvn39JQQAAAAAqGdZXDEaQhg4cODy5cu/8pWvJA64aS6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kLpvy6KOPymQywwfoV8+JEyc+8sgjtObs7ubNm7t27dqzZ09ycnJiYmJ2dravry/3IYB9\n7JIIgUajkclkXQ5C3NJ54cIFw5+ZuLskEgn1q/hDPzFRPWE2fHarJwjfqDERPqPVE5bDR/XG\nDeEPnD6qJwgf6EH1A4rdwz25x/BNp3psjMK/Cfb6F/X19c3NzZaWlsRgyIqKimvXrnVf4qVS\n6cyZMwMDAykN24Oqqqr169crlUqZTBYcHGxvb69QKM6dOzd27FjuutGGq+eQIUNGjRpFe+R/\nq6io2LBhQ2Fh4dSpU7svnSNHjjx9+nRJSUmXn5mAIYKtnjAePrvVE4RvApgIn7nqCcvho3pT\nINjwjftwTxA+0CPY6gkO9/Qg/N5gYxT+Q2jXv2hoaNi9e/eePXtSU1ODg4Otra1JP97+kkgk\nlObtgVar3bRpk1qt9vPze//992fNmtXW1paVldXR0eHt7a1fJbnVc/jw4bNmzaI7sKG2traU\nlBSFQqFSqbovnc7OzomJie3t7dzSGRQURGtOeBBCq56wHz7T1ROEbxqYCJ+h6gnj4aN6EyG0\n8E3kcE8QPtAjtOoJDve0IfzeYGMUfkc417/QaDRr167Nz8+3s7N7/PHHvb29e/wEZ8H+agDn\n5MmTycnJHh4esbGxdnZ2SUlJ8fHxhJDo6Oh58+ZptVr9YiQWiz09PakO25WVldXUqVMzMjJ6\nXDpbW1u/+eabJUuWVFVVBQQEjBs3juKo8CCEUz0xivCZrp4gfJPBRPisVE8YDx/Vmw7hhG9S\nh3uC8IEe4VRPcLgXAITfG2yMghBptdqYmJjKykp/f/8dO3ZMnjy5y7U5WFk99+/fr1ar161b\n5+HhkZSUtG/fPp1OFx0dPX/+fELIqVOnUlJSJkyYQHvMXvWxdB46dOjq1atPPPHEsmXLJk6c\nSHdOMA7GET7r1ROED/zqO3wmqifsh4/qgU843AsEwgc+4XAvEAi/R8L6YC8AzunTp8vKypyd\nnbdu3SqXy3t8jEwm27Ztm7+/f3FxcWpqKs8T9lN9fb1YLA4ICDh16lSXdbOzszMhIeHo0aPl\n5eW0x/wPnU537dq17777TqfTcbc4OjrGxsa6uLikpqa+++67NTU17e3thw8fPnDggIWFxbhx\n4ww/fxPgQRhH+MxVTxA+UHXX8IVfPTGK8FE98AaHe1pwuAeKcLinBeH3hxntAQB6cOHCBULI\nokWLevwQt7q6Om4x5VbPX375RTgX79DpdIZXKXZ2di4uLv7yyy+PHDliuG4SQr744ouKioqA\ngAAPDw9Kw3al0Wji4uIKCgoIIY2NjVFRUdzt3NK5efPmy5cvR0VFSSQSrVZLCHnxxRft7Oxo\nTgzGxTjCZ6t6gvCBtv6EL8DqiTGGj+qBHzjcU4HDPdCFwz0VCL+fcMYoCNHNmzcJIcOGDet+\nV3Fx8bp16zQaDfc/ZTKZcNZNlUq1ZcsWw1vCw8MJIYcPH+6ybiYnJyckJJiZmS1btoz/OXtU\nXV391ltvFRQUODk5xcTEvPDCC4b3Ojo6fvDBBxEREWKxWKvV2tjYvPbaa3PnzqU1LRgl4wif\noeoJwgcB6Gf4gqqeGG/4qB54gMM9/3C4B+pwuOcfwu8/nDEKAtLU1MR9JKWTk1NZWVlZWdmY\nMWO6PObIkSMajeb69eszZ86kMWNfPvvss6tXr165ciUwMJC7JTQ0dPz48ZcvX3ZwcPDx8dHp\ndDdu3Dh06NCPP/5ICFmxYoWPjw/Vkf9Nq9W+9957N2/eHD16dExMTI8nz9va2r755pvLly+/\nefOmm5ububk5/3OC8dFXT4wlfFaqJwgf6EH4FN01fFQPA8TIfs43puoJwoeBgcM9RQj/nuDD\nl4CmrKwsS0tLS0tLQohKpVqzZo2ZmZmvry8hJC0traSkJDw83PBk+59++un777+3trZ+7bXX\nzMwEt61vZmaWmpra0NAwffp0/Y1BQUG5ubkqlSo5Ofm77747evRoUVGRRCJZvnx5ZGQkxWkN\npaamnjhxQi6X79y5k1s029vbf/jhh/j4+MTERLFYrF/ipVKpg4ODRCKhOi8wrI/qibGEz0T1\nBOEDjxA+3WkN9TN8VA8Pzuh/zjey6gnChweGwz3daQ0h/HuCjVGgJicn5913383MzAwJCamt\nrY2Jiamrq+vo6IiIiBg+fLhCoSgrK0tLS3N1dXV2dq6pqTlw4MCBAwcIIW+++aaXlxft8Xsw\ndOjQM2fOFBUVhYeH66/NYW5uPmPGDJlMptFoGhsbra2tp0yZsmbNmilTptCd1tCpU6cKCgoi\nIyODgoIIIcXFxVu2bLlw4YK7u3tJSUlGRsaIESOGDh1Ke0xgXh/Vi0SiYcOGGUf4TFRPED7w\nBeHTHvZ3ED7wwxR+zkf1AIZwuKc97O8g/Hsi0n80FQDP2traYmNjL1265O7u3tzcXFdXFxAQ\nsHnzZqlUSghpamravn17Xl6e4V8RiUQvvvjiggULKI18dwkJCZ999llkZOTKlSu739vlo5mE\nIykpae/evcOGDYuOjs7IyPjxxx8nTpy4atWqwYMHf/nll4cOHZo7d+6KFStojwnM67t6Yozh\nC7Z6gvCBLwhfUBA+8MPUfs5H9QA43AsKwr8nOGMUqJFIJCEhIQqFoqioqKWlZdy4cVu2bNGv\nmxYWFhEREZaWllVVVY2Njebm5uPHj1+9enVYWBjdsfvm6el54sSJ0tLSyMhICwuLLvcKdt0c\nMWJEWVlZbm7u2bNna2pqVq5c+fzzz3O/43D8+PHKysrQ0FB/f3/aYwLz+q6eGGP4gq2eIHzg\nC8IXFIQP/DC1n/NRPQAO94KC8O+J4C7iACalvr5epVLp/9zc3Gy4dJqZmS1atGjRokXt7e1m\nZmZCW3dUKlVWVtacOXMML5JiZWU1a9as48ePJyUlLVq0iOJ4d1VXV6dWq+Vyuaurq0QiiYmJ\nyc/Pb29v9/Pz0193OSkpKTMzUyqVzpgxg+60YDT6rp4g/AGG8IEKhE+RYfWEEIQPvMHP+RTh\ncA9U4HBPF8K/b/hVeqCpo6Nj586dLS0tZmZmly5d8vDw+POf/yyXy2nPdXe3bt16/fXX6+rq\nZDLZ7Nmz582b5+Liwt1VVVW1YsUKR0fHTz75RCwW052zRzdv3vz444/T09O5/EeNGvXaa68N\nGzbM8DE6ne7gwYPffvutTqd79dVX58yZQ2lYMDbsVk8QPsD9QvhU9Kd6gvBhwLAbPrvVExzu\ngSp2qycI37ThV+mBJrFYHBISEh4ePm3atKKiooKCguzs7JCQEO6T7Agh586dy8nJ0X+SnXDI\nZLLJkyd3dnaWlpbm5eUlJiaWlpYOGjTI2dnZxsamrKysoKBg2LBhnp6etCftqqqqav369Uql\nUiaTBQcH29vbKxSKc+fOjR071snJiRCi0+kyMjL+9re/paSkiMXiqKiouXPn0p4ajAe71ROE\nD3C/ED7/7lo9QfgwwNgNn9HqCQ73QBu71ROEb9qwMQoU6HS6nJyclJSU0aNHS/5PSEiIfvUM\nCgqysrJKTk7evXt3dnb2hAkTHB0daU/dlZ2d3eTJkyMjI21sbFQqlVKpPH369MWLF2UyWUBA\nwNmzZ2tra2fPnk17zN/RarWbNm1Sq9V+fn7vv//+rFmz2trasrKyOjo6vL29R40aRQhpbm7e\nvXt3UVHR8OHD33rrrWnTptGeGoyEPvyxY8eamZmxWD1B+AD3wjgO94TB8PtTPUH4MDCMI3zm\nqic43AM9xlE9QfgmDL9KD3zTaDRxcXEFBQWEkAULFkRFRenv0n+Sna2t7fDhw3Nycgghzz77\n7LPPPktt3P7RarUXLlw4fvx4fn4+IUQul9++fVur1X788cfcJb0E4qefftq3b5+Hh0dcXJyV\nlVVSUtK+fft0Ol10dPT8+fO1Wq1EIiGENDQ0FBQUTJw4UWiXfQF29RY+u9UThA/QJ6M83BNG\nwu9n9QThw8NmlOEzUT3B4R4oMcrqCcI3MThjFHhVXV29fv16lUrl5OS0evXqyMhIw4t0SCSS\nsLAwjUZTUFCg0WgkEkl0dPTixYspDmyora3t+PHj+/fvP3/+fFNTk7e3t354sVg8bNiw2bNn\nT5w4saWlpaioSKvVPvvss1OnTqU7cxf79+9Xq9Xr1q3z8PDosmgSQk6dOpWSkjJhwgSpVOrm\n5oZFEx6WPsIXePUE4QPcF2M93BNGwu9n9YQQhA8PkbGGz0T1BId7oIHp6gnCh/+DM0aBP1qt\nds2aNSUlJaNHj46JibG1te3tkQqFoqysbPz48foLHlNXVVW1bdu2iooK/S1eXl5vv/12j78F\nUFtbm5+fHxoayuOA/bJ69erS0tIjR44kJyfv2bPHcNHs7Ox85ZVXKioq9u7d6+HhQXtSMB79\nDF+A1ROED3BfTOdwT4QaPqoH/plO+MKsniB84B3T1ROEDwZwxijwJzU19cSJE3K5fOfOndy6\n2d7e/sMPP8THxycmJorFYh8fH+6RTk5OI0eOtLGxoTrvfzQ1Na1fv16tVru7u69atWrJkiXc\n4p6WlhYcHGxtbd3l8VZWVgK8KjMh5PLly+Xl5W1tbV999ZXhokkI+fzzzzMzMwMCAhYuXEh3\nSDAy/QxfaNUThA9wv0zncE+EGj6qB/6ZTvjCrJ4gfOAdu9UThA+/J777QwAeEu7KIzNmzODW\nzeLi4jfeeOPLL7+0tbWtrKzct29feno67Rl7tnfv3urqaj8/v//5n/8JCwsrKCj47bffCCEa\njWbTpk0ajYb2gH0xPCs8PDycEHL48OEui2ZycnJCQoKZmdmyZcuoDAlGDOFTgfCBIlRPBaoH\nuhA+FQgfKGK3esJy+F1+5xvhPxTYGIUBV1FRER8fr9Vqu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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow across all three target wikis on wikitext broken down by experience\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_editcount %>%\n",
" filter(editor_interface == 'wikitext') %>%\n",
" group_by(step, edit_count_bucket, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_byeditcount) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'red4') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.05, lab=c(\"total users: 4\",\"total users: 31\",\"total users: 52\", \"total users: 25\", \"total users: 114\"),\n",
" edit_count_bucket= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\" )), vjust=1) +\n",
" facet_grid(~edit_count_bucket) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Wikitext Reply Tool Workflow Funnel by Editor Experience \\n Across All Opt-Out Wikis\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/wikitext_reply_workflow_overall_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 286,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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i/2NKO0qPv3709/DmEHSEtLS0tLq6qqItrvLkoIsbe3pxv37t2TGaC6upoZ198Y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\n1dWEEEtLyx49ejD7P/roI6FQaGtrq8Fka+OcAAAA0KigYRQAAAC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OSWq91OT999+/8847N2zYMGjQ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\nUjJmzJiYmBg7O7vbnZmfn19WV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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow across all three target wikis on VE broken down by junior and senior contributors\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_experience %>%\n",
" filter(editor_interface == 'wikitext') %>%\n",
" group_by(step, experience_level, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_byexperience) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'red4') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.05, lab=c(\"total users: 87\",\"total users: 117\"),\n",
" experience_level= c(\"junior contributors (< 100 cumulative edits)\", \"senior contributors (> 500 cumulative edits)\")), vjust=1) +\n",
" facet_grid(~experience_level) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Wikitext Reply Tool Workflow Funnel for Junior and Senior Contributors \\n Across All Opt-out Wikis\"\n",
" ) +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/wikitext_reply_workflow_overall_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Compared to Visual Editor, a smaller percentage of contributors users that successuly load the editing interface (step = `ready`) start typing a comment (step = `firstChange`) using wikitext. For editors with 1 to 4 cumulative edits, only 48% of users that clicked the reply link and reached ready started typing a comment. \n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Workflow funnel for each opt-out wikis by user's experience level"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We also reviewed the worflow funnel for each individual wiki to confirm any differences on a per wiki basis. "
]
},
{
"cell_type": "code",
"execution_count": 287,
"metadata": {},
"outputs": [],
"source": [
"# Find total init sessions for each target wiki by editcount\n",
"\n",
"init_users_bywiki_editcount <- reply_users_workflow_funnel_clean %>%\n",
" group_by(edit_count_bucket, editor_interface, wiki) %>%\n",
" filter(step == 'init') %>%\n",
" summarise(init_users_editcount = sum(n_users), .groups = 'drop')\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join with workflow table\n",
"reply_users_workflow_funnel_forplot_bywiki_editcount <- inner_join(reply_users_workflow_funnel_clean, init_users_bywiki_editcount)\n"
]
},
{
"cell_type": "code",
"execution_count": 289,
"metadata": {},
"outputs": [],
"source": [
"# Find total init sessions for each target wiki by experience level\n",
"\n",
"init_users_bywiki_experience <- reply_users_workflow_funnel_clean %>%\n",
" group_by(experience_level, editor_interface, wiki) %>%\n",
" filter(step == 'init',\n",
" experience_level != 'NA') %>%\n",
" summarise(init_users_experience = sum(n_users), .groups = 'drop')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join with workflow table\n",
"reply_users_workflow_funnel_forplot_bywiki_experience <- inner_join(reply_users_workflow_funnel_clean, init_users_bywiki_experience)\n"
]
},
{
"cell_type": "code",
"execution_count": 291,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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bgUDg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\nz3aoxfb29vj4+B9//PH27du0x/wDrVZ78+b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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow on arwiki on VE broken down by edit count\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_editcount %>%\n",
" filter(wiki == 'arwiki',\n",
" editor_interface == 'visualeditor') %>%\n",
" group_by(step, edit_count_bucket, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_editcount) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 10\",\"total users: 29\",\"total users: 34\", \"total users: 14\", \"total users: 25\"),\n",
" edit_count_bucket= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\" )), vjust=1) +\n",
" facet_grid(~edit_count_bucket) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Visual Editor Reply Tool Workflow Funnel by Editor Experience \\n on Arabic Wikipedia \") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/ve_reply_workflow_arwiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 292,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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TQaFYrBhi6UtJL/fH5hAYAiaBgFAGljxoyhS38+ePAgMTHx9OnTtOcC7UyqwQst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\nYECbR/ft2zdy5EhtJ0otH374oUgksrGxaegLBQYGbt68mdTXMMp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UlZXt7Rb2XfH/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\nwYKysrJFixbFH2vTokWLOubMzc0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cEoAAAAABAdwSgAAAAAEB3BKAAAAAAQHcEoAAAAABAdwSgAAAAAEB3BKAAAAAAQHcEo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\nw+zZs6keE/pDLpfv3r1bLBbze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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow on arwiki on VE broken down by experience\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_experience %>%\n",
" filter(wiki == 'arwiki',\n",
" editor_interface == 'visualeditor') %>%\n",
" group_by(step, experience_level, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_experience) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 73\",\"total users: 29\"),\n",
" experience_level = c(\"junior contributors (< 100 cumulative edits)\", \"senior contributors (> 500 cumulative edits)\")), vjust=1) +\n",
" facet_grid(~experience_level) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Visual Editor Reply Tool Workflow Funnel by Junior and Senior Contributors \\n on Arabic Wikipedia \") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" p\n",
" \n",
" \n",
"ggsave(\"Figures/ve_reply_workflow_arwiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)\n"
]
},
{
"cell_type": "code",
"execution_count": 293,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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rK2b9++bNmyZ599dunSpePHj284cvDgwQUFBQ2XdOvWrYk933zzzYsXL164cGFubu60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\nQ5cuXb761a+WlpYWFRWtX7/+lltuOfvss+uH7dq16/bbb8/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vnnmZ/ZkG7+X3/9dcSIEW+99dbSpUuHDRtWVFRUVFTUfX4W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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow on arwiki on wikitext broken down by experience\n",
"\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_editcount %>%\n",
" filter(wiki == 'arwiki',\n",
" editor_interface == 'wikitext') %>%\n",
" group_by(step, edit_count_bucket, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_editcount) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'red4') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 3\",\"total users: 20\",\"total users: 34\", \"total users: 9\", \"total users: 31\"),\n",
" edit_count_bucket= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\" )), vjust=1) +\n",
" facet_grid(~edit_count_bucket) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Wikitext Reply Tool Workflow Funnel by Editor Experience \\n on Arabic Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/wikitext_reply_workflow_arwiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 294,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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XI08tYrppF0sacZpVndt29f+nMIO0BiYmJiYmJ5eTlp+O6ihBB7e3u68eDBA5kB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\nmlAojI2NldkwyjSt0msy+xsiLVrLH+14x5IDAAAAjRyG0gMAAAC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juefPLJmTNnrlmzpl69ev3797/gggu2GMxVfAdtr2O7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HhotT9j/o3dhCXeJsa/pi1xPZAzXpPnpB0FTtqHVbtm5sE06IcvnXLKKSGENWvW7LN9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\n41/9EYxyZA6bjdLoHGI4DiE0b968X79+l112Wb9+/SorKzd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mzPgXKQebHtvxOgAAIABJREFUAHX5+BOM8v+oOxy3b9++V69eya6Io9Kv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\ntbUdOnRoQECARMOi4UpLS5csWZKXl2dnZxcUFNSqVavs7Ozjx4/36tVL/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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow on arwiki on VE broken down by experience\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_experience %>%\n",
" filter(wiki == 'arwiki',\n",
" editor_interface == 'wikitext') %>%\n",
" group_by(step, experience_level, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_experience) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'red4') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 73\",\"total users: 29\"),\n",
" experience_level = c(\"junior contributors (< 100 cumulative edits)\", \"senior contributors (> 500 cumulative edits)\")), vjust=1) +\n",
" facet_grid(~experience_level) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Wikitext Reply Tool Workflow Funnel by Junior and Senior Contributors \\n on Arabic Wikipedia \") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" p\n",
" \n",
" \n",
"ggsave(\"Figures/wikitext_reply_workflow_arwiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 295,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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DfN6lcGOUjGlvbgAAIABJREFUfXv37h0wYMDbb7+9YsWKQ2ZfCKGgoKBv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\n+vaFhIRMnDiR1px9amlp+eSTT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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow on cswiki on VE broken down by experience\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_editcount %>%\n",
" filter(wiki == 'cswiki',\n",
" editor_interface == 'visualeditor') %>%\n",
" group_by(step, edit_count_bucket, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_editcount) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 4\",\"total users: 18\",\"total users: 24\", \"total users: 9\", \"total users: 8\"),\n",
" edit_count_bucket= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\" )), vjust=1) +\n",
" facet_grid(~edit_count_bucket) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Visual Editor Reply Tool Workflow Funnel by Editor Experience \\n on Czech Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/ve_reply_workflow_cswiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 296,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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VsKaQ630GSUKAYbu1DSSP5z+YUFALKgYRQAxI0dO5Yu/fnw4cOkpKQzZ87Qngu0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\nxMTIChMbGysSieh2YmJiQ0OD1GB1dXXJycl028fHR63JBAAAAAD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ZG3cwx0OQa1MpUdeTKurKysqKgw/kXLkSQSGh0DXY6BLkfi6Aezhh2MNm3aNPzPeaPV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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow on cswiki on VE broken down by experience\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_experience %>%\n",
" filter(wiki == 'cswiki',\n",
" editor_interface == 'visualeditor') %>%\n",
" group_by(step, experience_level, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_experience) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 46\",\"total users: 14\"),\n",
" experience_level = c(\"junior contributors (< 100 cumulative edits)\", \"senior contributors (> 500 cumulative edits)\")), vjust=1) +\n",
" facet_grid(~experience_level) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Visual Editor Reply Tool Workflow Funnel by Junior and Senior Contributors \\n on Czech Wikipedia \") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" p\n",
" \n",
" \n",
"ggsave(\"Figures/ve_reply_workflow_cswiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 297,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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SMV5Obv70+TbdmyRQuFhSauU6dOHOXoJtpVV1cXGhoaGhq6fft2HdxOHY2t6gAA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\nVKo6cUZGRpGRkTS+lpmZSQjhcrnHjx9XUKWULtuaOHY1psG7q9Q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oULprORo//vGPFy9e/MQTT3Tp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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow on cswiki on wikitext broken down by experience\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_editcount %>%\n",
" filter(wiki == 'cswiki',\n",
" editor_interface == 'wikitext') %>%\n",
" group_by(step, edit_count_bucket, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_editcount) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'red4') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 0\",\"total users: 8\",\"total users: 4\", \"total users: 11\", \"total users: 32\"),\n",
" edit_count_bucket= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\" )), vjust=1) +\n",
" facet_grid(~edit_count_bucket) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Wikitext Reply Tool Workflow Funnel \\n on Czech Wikipedia by Editor Experience\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/wikitext_reply_workflow_cswiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)\n"
]
},
{
"cell_type": "code",
"execution_count": 298,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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Cl/rEqo9oHVSHZU8tTLppJ8sacZpUU9dOhQ+nMIO0BSUlJSUlJ1dTVp/uGihBAr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\n3rHsAAAAwNsCHaMAAAAA74LQ0NBVq1bRz127dv3xxx+Dg4MNDAz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3766YwZMxo3bhzvWagu77///nPPPXfrrbdeeuml8Z6F6lJUVHT77bf36dPn3nvvjfcs\nVKMnnnhi1apVzz//vGuG6rC333575syZd9xxx+DBg+M9S43WuXPnBg0aHPYlZ4weXlpa2lHO\nJiAIgnr16iUlJaWnp8d7EKpR7LvgjDPO6NmzZ7xnobrs2bMnCIIWLVr4dq7bIpFIcnKyVa7b\nmjZtGgRB165dO3fuHO9ZaqUGDRr4Hjm6WB/ao0eP2BcbddK6deuCIGjbtq1vhzqssLAwCILG\njRtb5bqtUaNGQRD07NnzSH0QdcDKlSuDIGjXrp1v5+/MfQMBAAAAgNBxxijfUZs2bdzFuc5r\n1qxZ+/btk5KS4j0I1Sg5Obl9+/apqanxHoTq1a5du+bNm8d7CqpXWlpa+/btPUiN6tO8efP2\n7dt7JGPd1rBhw/bt27tbQt0WiUTat28vGNR5LVq0cNCu8xo3bty+ffuGDRvGe5BazD1GAQAA\nAIDQ8asDAAAAACB0FKMAAAAAQOgoRgEAAACA0FGMAgAAAAChoxgFAAAAAEJHMcpJsG/fvniP\nAMC35aANnDhHEoBaxEEbjkQxynexfPnyXbt2xT7esmXLz372s3nz5sV3JKpVRUVFvEcAvjsH\nbeDEOZKEkAQItZeDNnxLilGO28qVKx9//PEHH3xw165dW7ZsmThx4q5duz766KPy8vJ4j0a1\n2LJly6OPPhrvKYDvyEEbOHGOJCEkAULt5aAN317ir371q3jPQC2Tlpa2bt26tWvXLlu2LDMz\nc9euXX369HnooYeSkpLiPRrV4umnn87Ozr7gggvS0tLiPQvVaNeuXRs3biwrK2vSpEm8Z+Fk\nctAOm4qKipUrVy5atOjMM89MSEiI9zjUEY4kISQBhoH4V1c5aIeN+HciFKMct8TExEGDBuXk\n5Kxfv764uPjss89++OGHk5OT4z0X1aWioiIrKysxMfH888+P9yxUi3/84x9Tp0595plnFixY\nMH/+/Ozs7J49ezZr1izec3FyOGiHSkFBwaRJk/785z+vWLGiuLj43HPPjfdE1BGOJCEkAdZt\n4l/d5qAdKuLfCXIpPcfwxRdf3HPPPTt37qy6cffu3Vu2bKn8uKioKB6jcYpkZGSkpqYuWrSo\npKQk3rNw8uXn599zzz0ffvhhcnJyRkbG2WefnZub+8tf/jInJyfeo3HSOGiHxPbt23/5y1+u\nXbu2ZcuWEydO/MlPfhLviajFDk2AjiRhIwHWYeJfGDhoh4T4d+KcMcox/Od//ueyZcuCIOjX\nr1/lxuTk5JycnObNm7dv337t2rXZ2dmDBg1q0KBB/MakGiUmJu7Zs+ezzz7r1KnT6aefHu9x\nOJmi0eiECRPy8vJ69er15JNPXn755SUlJcuXLy8rK+vatWuPHj3iPSAnh4N2GESj0Yceemjb\ntm1nnnnm5MmTu3TpEon4/Tff3aEJ0JEkbCTAukr8CwkH7TAQ/04KxSjHcP755zdp0mTUqFFV\nv8EikcigQYMuuuiiIUOGrF+//tDj7Hvvvbdy5cqePXvGaWpOsjZt2syfP3/fvn2XXnppvGfh\nZHrrrbcWLFjQsWPHyZMnp6amZmZmzpgxIwiCMWPGXHPNNdFo1L+sdYODdhgsWbLkL3/5S1pa\n2hNPPBG7VVxpaembb745Y8aM+fPnRyKRbt26xXtGapNDE6AjSQhJgHWS+BcSDtphIP6dFA55\nHENiYuK1116bmJgYBMGWLVsqr6iqV69e/fr169evP2HChH79+m3evPnBBx/csWNHEAQLFiyY\nOnXqc889t3bt2niOzreQl5dXUVFRdcuWLVtef/31PXv2VN3Ypk2bfv36rVixYvv27ad2QKrX\nRx99FATB2LFjGzZsmJmZOX369IqKijFjxlx77bVBECxYsOD3v/99vGfk5HDQrvNiy3fJJZfE\nYvGGDRvuvvvuP/7xj02aNNm2bdv06dOzsrLiPSO1yWEToCNJ3XBo/AskwDAR/8LDQbvOE/9O\nCmeM8m0VFBTcf//9ixYtGjRoUMOGDSu3x+7rHPsd1MKFCz/++ON58+ZVVFT80z/909ChQ+M3\nL8f2xRdf3H///V999dXAgQNjj67bs2fPvffe++GHH86bN2/r1q1paWktWrSI7dyoUaNFixY1\nbNiwT58+cZ2ak2nOnDnffPPN3XffvWDBgmeffbZqLC4vL/9f/+t/LVu2LCMjo2nTpvGelOMW\njUZXrFixZs2alJSUxo0bV2530K6rvv7662XLlhUVFbVv337u3LnTp0/v2bPnpEmThg0bVlxc\nnJOTk5qa6gkqfAeHTYCOJLXXofEvkABDRvyrw8S/sBH/TgrFKN9WSkpKbm5uTk7O0qVLD+1G\nMzIyCgoK1q5dW1BQkJiYOGbMmOuvvz6O0/JtFBcXL1q0KCcnJz8/PxaOk5OTY5dXbN26NScn\n5+233/7oo48SEhI6dOjQqVOnhQsXfvHFF9dee21ljKa2++STTzZv3lxSUjJz5syqsTgIghde\neGHZsmV9+vQZMWJEfIfkO8jLy5s4ceLs2bM//PDD+fPn79y5s2/fvrEzvwIH7bqioqJi5cqV\nixYtOvPMMxMSEs4444xNmzatWrXq3Xff3bFjxx133PHjH/849o/1vHnztm3bNnjw4PT09HhP\nTe1zpAToSFJLHRr/giCQAENF/KurxL8wEP+qQ8Khl1HAkUSj0SlTpnzwwQdt27adPHly8+bN\nD9ohJydn06ZN5557bps2beIyIccrLy9vwoQJO3fuHDp06Pjx4yvzbnl5eXZ2dmZmZnZ2djQa\nbdiw4SWXXLJ///6FCxf+6le/qvokLmq1JUuWPPnkk7GPq8biBQsWTJs2rV69er/5zW/cmKbW\n2bt37/jx47dv356cnNyuXbvNmzeXlZX17t37kUceSUlJqbqng3btVVBQMGXKlNj1U8OHDx89\nenRs+5o1a0pLS3v16pWUlBTbkpmZ+eyzzyYnJ//Hf/xHWlpa3CamNjt6AnQkqXWOFP8CCTAc\nxL86SfwLA/GvmjhjlOMQiUQuvPDCzZs3H/a80SAIWrZs2b1796on7VPDNWnS5IILLvjwww8P\nOnEgISGhffv2F1100ZVXXtmkSZOtW7d+8sknGzduDIKgtLQ0IyMj3oPzXWzZsuW//uu/+vXr\nV/kjUKdOndasWZOfn9+sWbNrr722RYsWX3/99cyZM1966aUgCMaNGzdgwIC4jsx38dprr2Vl\nZaWnp//mN78ZMWLExRdfvHLlynXr1q1evTojI6NevXqVezpo11Lbt2+/7777tmzZ0rJly/Hj\nx//gBz+ofFBGixYtWrduHTs9pKKi4k9/+tOLL74YBMG4cePOOuusOM5MrXb0BOhIUuscKf4F\nEmBdJP6FhPhX54l/1UcxyvE5ZjdKrXOUcBwEQYMGDXr37n311Vf37t27tLR027ZtW7duveqq\nqw76xSO1wq9+9ausrKyDVvmCCy5YtWrVli1bFixY8Morr8yZM2f9+vWJiYm33XbbD37wg/gO\nzPHaunVrJBKZPXv2/v37p0yZkpqaGgRB48aNMzIyPv3009zc3EPDMbVONBp96KGHtm3bduaZ\nZ06ePLlLly6HPj64oqLio48++u1vf7to0aJIJDJ69Ohhw4bFZVrqDAmwjjl6/AskwDpE/Kvz\nxL8wEP+qlWKUIzrSnZsl47pn//79nTp1+vTTT9etW3fYcJyQkNCmTZvBgwd36NBh8eLFjRo1\n6t27d7ym5bvJz89v0aLFZ599dtAqJyUlXXLJJSkpKQUFBXv37m3UqNGAAQN+8YtfOFmg1snL\ny3vggQeysrKi0eg555wzePDgypeSk5MHDx4sHNcNS5Ys+ctf/pKWlvbEE0/EnkBaWlr65ptv\nzpgxY/78+ZFIpFu3bkVFRdOmTVu/fn3nzp1/+ctfDhkyJN5TU5tIgCFxzPgXSIC1n/hX54l/\nISH+VSv3GOXw8vLyJk+e/OWXXwZBkJCQ8L3vfW/s2LH169ev3OGY9xulVvj666+nTp26cuXK\nqhsPveFUpeLi4ptuuqlTp07/+3//71M1Iyfq66+/fvrppz///POqGw+7yhUVFZ6rUHsVFxc/\n8sgjOTk5QRD84Ac/uOOOOw7aobCw8KGHHvriiy969+796KOPCse11PPPPz937tyRI0fecsst\nQRBs2LDhqaeeKigoSE9PX7VqVVlZ2YQJEwYOHFhYWLh27drzzjvPNzXHRQIMg+ONf4EEWAuJ\nfyEh/oWE+FetnDHKYezdu/f+++/funVrcnJyp06dCgsL161bt2rVqqq/Zap61kDr1q179OgR\n35n5Dnbt2nXPPfds2rTpjDPO+NnPfjZixIj27dvn5uYe5cSB0tLS1157rbCw8Oabb47LzByv\n2Cp/+eWXZ5xxxr/+67/eeOONHTp0yM3Nzc3NPXSV/Qtaq9WrV2/IkCGff/75jh07tm/fftll\nlx10wWPliQPnnXfeOeecE685OUFff/31smXLioqK2rdvP3fu3OnTp/fs2XPSpEnDhg0rLi7O\nyclJTU09//zzY89e8E3NcZEAw+A7xL9AAqxtxL/wEP9CQvyrVopRDuNb3rk5low7d+58+eWX\nx3dgvpvnn3/+888/79q16xNPPNG5c+fTTjutV69eF1544d///ve1a9ceGpvKy8unTp365Zdf\n9uzZ83vf+14cJ+fbe+6551atWhVb5dNPP71Zs2Y9e/YcOHDgkVaZWq0yHG/dunXFihUZGRlV\nz/MKgiA5OfnSSy/t27dvvCbkxJ1xxhmbNm1atWrVu+++u2PHjjvuuOPHP/5x7IrmefPmbdu2\nbfDgwenp6fEek1pJAgyD441/gQRYC4l/oSL+hYH4V60Uo/w/jvfOzZFIpFOnTnEdme/umWee\nOXDgwM9//vMOHTpUbkxNTW3VqtWSJUs2bdp0UGzatm3bH//4x6SkpIkTJzZt2jROU3N8Yqt8\nzz33tG/fvnJjampqmzZt/v73vx+6ytR2leE4Nzf3008/PTQcxx5YSe0ViUQuuuiic889d+jQ\noaNHj+7atWtse2Zm5uzZs5OTk++6664GDRrEd0hqHQkwPI43/gUSYC0k/oWN+FfniX/VSjEa\nUl988cXjjz9+3nnnVb1rvjs3h83LL78cjUZ/+MMfNmrUqOr29u3b//nPfw6C4KDYlJqa2qdP\nn0suuaRLly7xmZjjF1vlH/3oRwc9IqNDhw6vv/56eXn5pk2bDhw4cO6558ZrQk7Qrl27Nm7c\nWFZWFrsRe/AtwjG1zqGr3KJFi9atW8d+zqmoqPjTn/704osvBkEwbty4s846K46jUpMdNv4F\nEmDIHG/8CyTAWkj8q/PEvzAQ/06ZSLwHID7+8pe/5Obmzp49u+rGtLS0Nm3abNiwITc399Df\nHzZp0uTRRx/t0qXLqlWrJk2aVFZWdgrnpVrEzvVYs2bNQdtLS0srKipGjBjRvHnztm3bVv1i\n6NGjh7uJ1S6xVY7dkb2qkpKSaDR63XXXNWnSZPbs2Qfdm59a4R//+Me//du/3XLLLffff//t\nt98eu5tY7KWUlJRJkyalp6dv2LDhoYce2rt3b3xH5Ts7yioHQVBRUZGVlXXvvff+n//zfxIS\nEn76059eccUVcZyWGu6w8S+QAEPmO8S/QAKsbcS/Okz8CwPx7xRzxmhInX/++U2aNBk1alQk\n8n/LcXduDqFly5atW7du6NChVdf69ddfX7Fixfe+973bbrvtvPPOi+N4nBSxVb744ourrvIb\nb7zx6aefXn755eeee+5HH330zTffXHzxxXEckuOVn59/33335ebmpqSkDBw4sGnTpjk5Oe+9\n995ZZ53VsmXL4P89caBNmzbdunWL98gct2OuclFR0bRp09avX9+5c+df/vKXQ4YMiffI1GiH\njX+BBBg+4l8YiH91kvgXBuLfqacYDalIJNKzZ89YLN6yZUtpaWnsOgt3bg6Vrl27rlq1auPG\njR999FHXrl1btmxZVlY2e/bsWbNm1atX7/bbb2/WrFm8Z+REVV3lbt26tWjRIhqNVl3lVq1a\nzZ07t7Cw8Prrr4/3sHxb0Wh0woQJeXl5vXr1evLJJy+//PKSkpLly5eXlZV17dq18qSe2CG9\nbdu2fo1cG32bVa5fv/7gwYPPOuus0aNHt2rVKt4jU9MdKf4FEmCYiH9hIP7VSeJfGIh/cZFQ\nUVER7xmIp4KCgnvvvTclJWXy5MnNmzePbSwuLn7kkUdycnK6du366KOPNm7cOL5DcoJKSkre\nfPPN7OzsxMTE/v37X3XVVZW33963b9+kSZNil1OlpqYeOHDgwIEDQRDcfvvtw4YNi+fQHL9o\nNLpy5crdu3f36tWrTZs2ldurrnJaWtr+/fuLi4uD/17lzz777KGHHmrZsuXvf//7uI3Ocfrb\n3/42ffr0jh07TpkypWHDhpmZmdOnT6+oqBgzZsy1114bjUbdYr8OsMpUn8PGv0ACrHOOlADF\nv7pE/AsPwSAMrHJcOGM07FJSUnJzc3NycpYuXTpo0KCDzht15+Y6ID8///7773///fe3b9+e\nl5eXnZ29bNmy888/P7bW9evXHzp0aGJi4pdffllYWBiNRps1a3bHHXdceeWV8R6c45OXlzdx\n4sTZs2d/+OGH8+fP37lzZ9++fWP/cMZWORKJbNy4cc+ePWVlZU2bNh03btyVV14ZjUaffvrp\nHTt2XHbZZa6bq0VeeumlvLy8e++9t2PHjgcFpiAI3n777UWLFvXr1y/eY3JCrDLV57DxL5AA\n65ajJEDxr84Q/0JFMAgDqxwXzhgliEajU6ZM+eCDD9q2beu80Tpm3759//N//s/t27e3b9/+\nhz/8Ybt27Z5++ukvv/yyVatWkydPrnrifTQa3bZtWxAEHTp0OPTBC9Rwe/fuHT9+/Pbt25OT\nk9u1a7d58+aysrLevXs/8sgjVW8sVVZWtnXr1iAIOnbsGIlEioqKpk6dmpWVlZaWNm3atKZN\nm8bvHXBs+/btq3yC8Pjx4zdu3PjGG28sWLDgmWeeqRqYysvL77zzzq1btz777LMdO3aM68ic\nEKtMtTpS/AskwDrhWyZA8a9WE//CQPwLG6scF84YJYhEIhdeeOHmzZuPct6oOzfXUlOnTs3J\nyenVq9fkyZO7deuWlZX1zjvvBEGwb9++rKysgQMHVv5DG4lEmjZt2rRpU7G4NnrttdeysrLS\n09N/85vfjBgx4uKLL165cuW6detWr16dkZFRr1692G6RSKRZs2bNmjXbs2fP3/72t9/+9rdr\n165NS0t7+OGH27ZtG9+3wKGWL1/eoEGDBg0aBEGwZcuWX/ziF/Xq1evZs2cQBJ988snmzZtL\nSkpmzpxZNTAFQfDCCy8sW7asT58+I0aMiOf0nDCrTLU6UvwLJMA64VsmQPGvVhP/6iTxL+Ss\nclwoRgmCY3Wj7txcS23evPnf//3f09LSHn/88dTU1MzMzBkzZlRUVIwePToxMXHdunUHdaPU\nRlu3bo1EIrNnz96/f/+UKVNSU1ODIGjcuHFGRsann36am5t7UDiOOXDgwO9///u8vLwLLrjg\noYceateuXZzG54hWrlz561//etmyZYMGDdq5c+fEiRN37dpVVlY2dOjQhISESCSyZMmSnJyc\nIAiqBqYFCxb88Y9/rFev3r333nvaaafF9R1w3Hbv3l1UVBT7WSgIAqtMdTtmNyoB1lISYJ0n\n/tVV4l84VU2AVjkuFKP8/47SjXbp0iXe0/FdfPTRR0uXLh07dmzv3r2XL1/+1FNPxTLx8OHD\nW7Ro8c477xx63ii1S15e3gMPPJCVlRWNRs8555zBgwdXvpScnDx48OAjheOUlJSMjIyrr776\nqquuqmxhqFHS0tLWrVu3du3aZcuWZWZm7tq1q0+fPg899FBSUlIQBJ06dVqzZk1+fn6zZs2u\nvfbaFi1afP311zNnznzppZeCIBg3btyAAQPi/Q44DoWFhdOmTXvmmWeWLFlSeUy2ypwCR+9G\nJcBaSgKs28S/Okz8C5tDE6BVjgvFKP/XUcIxtVHXrl0TExOvvPLK0tLSBx98sLi4+MYbb7zp\nppuCIMjLy3v33XcHDhy4du3a1q1bx67OoNZJSkpavnx5bm7uzp07e/Tocf7551d99aBwHLsB\nf9VXfYPXZImJiYMGDcrJyVm/fn1xcfHZZ5/98MMPJycnV+5wwQUXrFq1asuWLQsWLHjllVfm\nzJmzfv36xMTE22677Qc/+EEcJ+d4FRQU3HPPPWvWrElNTb3qqqu6du1a+b1plTkFxL+6RwKs\n28S/Okz8C5UjJUCrfOopRvl/VA3HrVu37tGjR7wn4oT07t07MTHxvffeW7RoUa9evX7xi1/E\n7iH10ksvffnll//2b//Wq1evyy67LN5j8h1V3gZux44d27dvv+yyy6reaz+oEo7PO++8c845\nJ15z8t3s3LnztddeKy4uDoIgOTl5yJAhVc/vSEpKuuSSS1JSUgoKCvbu3duoUaMBAwb84he/\n8Gvk2iUajU6cOHHbtm3p6emPP/54//79q/7IapU5NcS/ukcCrMPEv7pN/AuJoyRAq3zqeSo9\nhxGNRrOysqpel0FtsWvXrry8vLS0tKo3U//P//zPV1555Z//+Z9vvvnmIAgyMzOfffbZdu3a\n/e53v4vfpJw0x3x8cElJSf369eMyGyeirKzsiSeeKC4urlev3scff9yxY8fHHnssLS3t0D0r\nKio8N6OWeuutt5555plWrVpNmzbt6GfxWGWqm/hXex02/gUSYJ0m/tVV4l9IfMsEaJVPDWeM\nchiRSKRTp07xnoLj849//GPq1KnPPPPMggUL5s+fn52d3bNnz2bNmgVBUFxc/P777+fn5zds\n2HD+/Pn/9V//FQTBv/zLv3Ts2DHeU3MSVH188KeffpqRkXFQDk5MTIzXbJyISCQyaNCgiy66\naMiQIevXr1+7dm12dvagQYMqTxx47733Vq5c2bNnT4Gp9po1a1ZeXt6PfvSjM88889BXd+3a\nVbncVpnqJv7VRkeJf4EEWKeJf3WV+BcS3zIBWuVTQzEKdUF+fv59992Xm5ubkpIycODApk2b\n5uTkvPfee2eddVbLli3btWu3ZcuWNWvWLF26dOPGjQkJCbfccovnzNZGJSUl8+bNe+mll95/\n//19+/Z17do1dt+oY4ZjaqlIJJKYmBi74VRlOL7gggsaNmy4YMGCadOmZWdn9+vXr0WLFvGe\nlO/o9ddf37179/XXX9+qVauDXtqwYcPDDz/s6SjAkRw9/gVBIAHWDeJf2Ih/YSAB1iiKUaj1\notHohAkT8vLyevXq9eSTT15++eUlJSXLly8vKyvr2rVrjx49EhISLrzwwmbNmiUkJPTq1euO\nO+646KKL4j01xy0/P//+++9///33t2/fnpeXl52dvWzZsvPPPz928YVwXDdEo9EVK1asWbMm\nJSWl6mVxVcPxwoULP/7443nz5lVUVPzTP/3T0KFD4zcvJ2r58uXbtm3r1q3boXd1/MMf/rB6\n9eouXbqcccYZcZkNqMmOGf+CIJAA6wDxLwzEvxCSAGsUxSjUem+99daCBQs6duw4efLk1NTU\nzMzMGTNmBEEwZsyYa665JhqNRiKRhISE7t27X3zxxQMHDoydREDtsm/fvvvuuy8vL699+/bj\nxo278cYbc3JyNm3a9OGHH1b+OrFqOG7Tpk23bt3iPTXHJy8vb+LEibNnz/7www/nz5+/c+fO\nvn37Vl4Kl5iYmJGRUVBQsHbtmzmEbwAAIABJREFU2oKCgsTExDFjxlx//fXxnZkT9+GHH37x\nxRcXXXRR1TtM/e1vf3v11VcbNWr0r//6r/Xq1YvjeEDN9G3iXxAEEmCtJv6FgfgXWhJgzaEY\nhVrvpZdeysvLu/feezt27JiZmTl9+vSKiooxY8Zce+21QRC8/fbbixYt6tevX7zH5IRMnTo1\nJyenV69ekydP7tatW1ZW1jvvvBMEwb59+7Kysg4Kx23btnWhXK2zd+/e+++/f+vWrcnJyZ06\ndSosLFy3bt2qVasyMjIqU1HsydF9+/bt3r37mDFjzjvvvPjOzHeze/fuoqKi2K2jTj/99Mqf\nctu2bduqVasdO3a8/PLLL7/8chAEP//5z7t06RLveYGaSPwLA/GvzhP/wqNq/AskwBrGU+mh\n1hs/fvzGjRvfeOONBQsWPPPMM1VjcXl5+Z133rl169Znn33WjfZrr82bN//Lv/xLs2bNpk6d\nmpaWVvnzz+jRo1esWLF8+fJWrVpNnjz50DvUUIv86U9/+tOf/pSenv7AAw80a9YsPz9/8uTJ\nmzZt6t279yOPPJKSkhLvATkJCgsLf/e7333wwQfNmzev/J7dt2/fo48+unr16qp7JiQk3Hrr\nrcOHD4/TpEBNJ/7VeeJfGIh/YXDY+BdIgDWJM0ah1vvkk082b95cUlIyc+bMqrE4CIIXXnhh\n2bJlffr0GTFiRHyH5ER89NFHS5cuHTt2bO/evZcvX/7UU0/FYvHw4cNbtGjxzjvvHHTiALXL\n1q1bI5HI7Nmz9+/fP2XKlNTU1CAIGjdunJGR8emnn+bm5q5evbrqiQPUUgUFBffcc8+aNWtS\nU1Ovuuqqrl27xq6cql+//tChQxs0aJCfn793796kpKRzzz13/PjxGRkZ8R4ZqLnEvzpP/Kvb\nxL+QOFL8CyTAmkQxCrXS1q1bX3rppX79+kUikUgksmTJkpycnCAIqsbiBQsW/PGPf6xXr969\n99572mmnxXVeTkjXrl0TExOvvPLK0tLSBx98sLi4+MYbb7zpppuCIMjLy3v33XcHDhy4du3a\n1q1b9+zZM97DckRffPHF448/ft5551W9kVBeXt4DDzyQlZUVjUbPOeecwYMHV76UnJw8ePBg\n4bhuiEajEydO3LZtW3p6+uOPP96/f/+qXwaRSCQ9Pf2aa6654YYbbr755qFDh3rULHAo8S9U\nxL+6QfwLs6PHv0ACrDEi8R4AOG779u2bNGnSX//61z//+c9BEAwePPjcc88NgqBZs2bdunWr\nqKgoKCiYMWPGtGnTgiC4/fbb3YW9Dhg1alT9+vX//ve/7969u1evXv/jf/yP2PYFCxYEQXDn\nnXc+8MAD11xzTVxn5Bj+8pe/5Obmzp49u+rGtLS0Nm3abNiwITc3NyEh4aBPadKkyaOPPtql\nS5dVq1ZNmjSprKzsFM7LyfTOO+9s2rSpVatWjzzySFpa2pF2S0pKOvTLACAQ/0JJ/KsDxL8w\n+5bxL5AA400xCrXP3Llz8/PzzzrrrMorpO6777709PTdu3fff//9I0aMGDNmzF//+tfExMSx\nY8deeeWV8Z2Wkyg/Pz8Ign79+sX+4czMzFy0aFG7du2aNm164YUXxns6juFnP/vZmDFjbrnl\nlqobU1JSJk2alJ6eHgTB3//+/7V373FR1/nixz8zAwxyUUYBL6gggoK6hKKIggSG1sEs02zz\ncbYs0tRHtq65LipqmiUZe87ZOIrVPrqds6vpw1uACYl3ERDwLvfb6iA4AmIgksM4vz9mf7Mc\nQFMkvs7M6/kXfufL9CYzXnz8fj/fk7du3WrzWcY49vPz45IB03Xq1CkhxMyZM9tcKWBw8+bN\nbp8IgIkh/ywW+WfSyD9LRv6ZCm6lB0yJYTOaXbt2NTc3b9q0yfh/WGtr6/DwcFtbW41G09jY\naG9vHxgYuGzZssDAQGkHRifodLoLFy4UFBTY2to6ODi0fqm5ufn48ePV1dV2dnbJyck7duwQ\nQixevJhHK5gEuVw+fPhwuVwuhFCr1Vqt1vBH2PAw2UuXLlVWVl64cCEkJMTGxqb1JyqVysmT\nJ/v7+0szN7rCnj176uvrZ82a1f4pGaWlpWvXrmWTOAD3Q/5ZAvLPXJF/loz8MxUsjAImo/Vm\nNKNGjQoNDW39qlwuHzFixPTp01999dWXX345JCTEyclJqlHxMMrKyv7zP/8zMDCwdQZVVVXF\nxMTs27cvIyMjOTm5trbW399foVAYXh0wYIBarS4oKDh9+nR5eblMJnvjjTemTp0q0VeATtJo\nNCtWrDh27NjEiRPbxHFRUdG5c+fax7HxvwGYqJycnGvXrnl5eQ0bNqzNS1999VVeXp6np+eQ\nIUMkmQ3Ak4z8MzPkn8Ui/ywQ+WcqWBgFTIa1tXVOTk5RUVFdXd3gwYPvd+8Mu5OYii1btpw5\nc6Z1BjU2Nq5YsaKyslKpVA4ePLihoaG4uPjy5cvGbddlMtmECROcnJxkMpmPj8/ChQvb/IAE\nk2Bra1tUVJSfn3/69OmHj2OYELVavXv3bn9//9b/Q87IyCgrKwsNDW19O1VKSsquXbvs7e3f\nffdd7pUD0B75Z2bIP4tF/pk98s90sTAKmAzjN86amprr16+Hh4d3uFkJTEVgYGCbDNq9e3dm\nZqavr+8nn3zy0ksvPf300xcvXiwuLm79SEqZTObt7f30008HBQW5uLhI/UWgM+Ry+YQJE65e\nvUocm6t169adOnWqpqYmMDDQEMfu7u75+fkVFRUZGRn9+/d3dXWtqanZtm3btm3bhBDvvfee\np6en1FMDeBKRf2aG/LNY5J/ZI/9MFwujgCkxfuOsqqq6ePEi3zhNWvsM2rdv3507d+Li4nr2\n7CmEcHBwCAkJOXfuXFFRUes4hhl4mDju168fzxQ2UX5+fhkZGZcvXzbGsUwmGz9+vCGOjx8/\nvnPnzqSkJMOzaKOiorgjEsADkH/mhPyzZOSfeSP/TBcLo4CJMX7jLC4u5i8VTV2bONbpdE89\n9VRwcLDxBKVSGRwcTBybpQfHcf/+/akl0+Xo6Dh+/Pg2cWxjYxMWFtajR4/q6urGxkZra+vR\no0cvXbo0JCRE6nkBPOnIP3NC/lky8s+MkX+mi4VRwPRww4U5af27WVtbO2zYsLFjx7Y+oU0c\nh4WFGZ5rCZNz8+bN8vLylpYWR0dHw5EHxDF31pi6DuNYLpf7+vpOnz795ZdffvXVV8PCwpyd\nnaWeFIBpIP/MCflnOcg/i0L+mSgWRgGTRBybkzbbhz3zzDO2tratTzDGcUBAwFNPPSXVnOi0\nurq6v/zlL5s3b05LS0tOTs7NzR0+fLjhwcH3i2OYFo1GY2tr2+anVkMcnzp1qnUcG15SKBQ8\nKQXAoyL/zAn5Z/bIP7NH/pkNFkYBU8VmNKauvr6+qampR48eotXvZmVl5YULF9r/qKNUKidP\nnuzv7y/RsOi86urq6OjooqIiW1vboKCgXr165efnHz16dNSoUYbnJ7SO4759+w4bNkzqkfFo\nKisrV6xYUVxcPGHChPZx7O3tfejQobKysjZxDACdQP6ZAWMBkn9mjPwze+SfOWFhFDBhbEZj\nohoaGuLj4zdv3pyenh4UFGRvby8e4jIQhUIh0bzoPJ1Ot2rVqqqqKh8fn02bNkVERNy9ezcn\nJ6elpWXo0KHGCDbEsYeHR0REhLQDoxPu3r177Nix/Px8tVrdPo5dXV2Tk5O1Wq0hjsePHy/V\nnADMA/lnutoXIPlnlsg/S0D+mRN2KgFMm62tLd9KTYtGo1myZMmJEyccHBwiIiJafxO1tbVd\nv369r69vaWnpmjVrGhsbJZwTXeLgwYNXrlwZNGjQunXrVCpVamrqZ599JoSYN2/etGnTdDqd\n8UyFQtH6wQswIc7Ozhs3buzXr196evqf//zn1r+tQoiff/75zp07r7zySp8+fQwXiQDAYyL/\nTNH9CpD8Mz/knyUg/8wJC6MA0H10Ot2HH35YU1Pj6+sbHx//6quvttl7mzg2M1lZWUKIt99+\n287OLjU1NSEhQa/Xz5s374UXXhBCpKWlffnll1LPiC7wgDjet29fS0uLh4dHfHz8nDlzJBwS\nACCVBxcg+WdmyD8LQf6ZDRZGAaD7HDp0qKKiwtXV9f3331epVB2e0zqO09PTu3lCdK36+nq5\nXO7n53fw4ME2WXzv3r19+/Z9//33V69elXpMPDK9Xn/hwoWdO3fq9XrDkdZx/MEHH9TU1Gi1\n2j179mzbts3GxuY3v/mN8XG0AABL84sFSP6ZE/LPXJF/5spK6gEAwIKcOnVKCDFz5swOHz15\n8+ZNQysb4vjkyZPcKGdy9Hp96+3VXV1dS0tLv/32271797bOYiHEN998U1lZ6efnN2jQIImG\nRSdpNJq4uLjCwkIhRGNjY1RUlOG4IY7XrFlz9uzZqKgohUJhuHbgzTff7Nmzp5QTAwAk9TAF\nSP6ZtNYFSP6ZJfLPjHHFKAB0n7q6OiGEu7t7+5dKS0uXL1+u0WgMv2T7MFOkVqvXrl3b+kho\naKgQYs+ePW2yOC0tbd++fVZWVm+88Ub3z4nHcf369T/96U+FhYUuLi4xMTFz585t/aqzs/Mn\nn3wSFhYml8t1Op2Dg8O77747bdo0qaYFADwJHrIAyT8T1aYAyT/zQ/6ZN64YBYBf3e3btw2P\nnndxcamoqKioqBg5cmSbc/bu3avRaC5dujR58mQpZkQX+Oqrr86fP3/u3Dl/f3/DkeDg4NGj\nR589e9bJycnLy0uv19+4cWP37t0HDhwQQixYsMDLy0vSkfFodDpdbGxsXV3diBEjYmJiOrw9\nytHR8b333ps/f35dXd2AAQOsra27f04AgOSM+ScoQHPXpgDJPzND/pk9x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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow on cswiki on wikitext broken down by experience\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_experience %>%\n",
" filter(wiki == 'cswiki',\n",
" editor_interface == 'wikitext') %>%\n",
" group_by(step, experience_level, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_experience) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'red4') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 12\",\"total users: 36\"),\n",
" experience_level = c(\"junior contributors (< 100 cumulative edits)\", \"senior contributors (> 500 cumulative edits)\")), vjust=1) +\n",
" facet_grid(~experience_level) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Wikitext Reply Tool Workflow Funnel by Junior and Senior Contributors \\n on Czech Wikipedia \") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" p\n",
" \n",
" \n",
"ggsave(\"Figures/wikitext_reply_workflow_cswiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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y3d9qzj777NNOO23t2rVZWVnt2rWLRCLffvvtjBkzevXq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\n17ZxHAAAAACA9teCYvRrX/ta++UAAAAAAEibF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vDgAAAAAAPqSsbgZzcnI++9nP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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot for huwiki\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_editcount %>%\n",
" filter(wiki == 'huwiki',\n",
" editor_interface == 'visualeditor') %>%\n",
" group_by(step, edit_count_bucket, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_editcount) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 0\",\"total users: 30\",\"total users: 22\", \"total users: 9\", \"total users: 7\"),\n",
" edit_count_bucket= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\" )), vjust=1) +\n",
" facet_grid(~edit_count_bucket) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Visual Editor Reply Tool Workflow Funnel \\n on Hungarian Wikipedia by Editor Experience\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/ve_reply_workflow_huwiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 463,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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UaJalDTlZJW8l+eX1gAIAs6RgFA3NixY+nSn/fv309OTj59+jQduUAHk6rxQgsW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\n7YqKivT09AEDBkgGS0tLq66uJoSYm5v37t2b2a+J3HiLclgeLex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4cOjcfi1atX33777X/4wx+aNWu2cePGSZMmzZs3L9Ezkkz2mwAdSVLDvvEvkADDRPwL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\niZmbo+GVV17Ztm3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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow on huwiki on VE broken down by experience\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_experience %>%\n",
" filter(wiki == 'huwiki',\n",
" editor_interface == 'visualeditor') %>%\n",
" group_by(step, experience_level, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_experience) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 52\",\"total users: 7\"),\n",
" experience_level = c(\"junior contributors (< 100 cumulative edits)\", \"senior contributors (> 500 cumulative edits)\")), vjust=1) +\n",
" facet_grid(~experience_level) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Visual Editor Reply Tool Workflow Funnel by Junior and Senior Contributors \\n on Hungarian Wikipedia \") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" p\n",
" \n",
" \n",
"ggsave(\"Figures/ve_reply_workflow_huwiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 300,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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ywsLCwsbNu2bVq4nCoa2qMDAAAARSEwCgAAAKBt/v7+9EV8fLy0NAkJCQKBgL5O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\nsrKSUay1tbW0Uzt27OjRo8eePXtkD6ukwQ6JLCwsZGSUTfWra+j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ABiRzEKAAAAAMSOYhQAAAAAiB3FKAAAAAAQO4pRAAAAACB2FKMAAAAAQOwoRgEAAACA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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow on huwiki on wikitext broken down by experience\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_editcount %>%\n",
" filter(wiki == 'huwiki',\n",
" editor_interface == 'wikitext') %>%\n",
" group_by(step, edit_count_bucket, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_editcount) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'red4') +\n",
" geom_text(aes(label = paste(round(pct_users*100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 1\",\"total users: 3\",\"total users: 14\", \"total users: 5\", \"total users: 51\"),\n",
" edit_count_bucket= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\" )), vjust=1) +\n",
" facet_grid(~edit_count_bucket) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Wikitext Reply Tool Workflow Funnel \\n on Hungarian Wikipedia by Editor Experience\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
"p\n",
"\n",
"ggsave(\"Figures/wikitext_reply_workflow_huwiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 462,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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l/D5qAdKuLfEXIpPV/js88+u+OOO7Zt21Z7444dOzZu3FjzcWlpaSJG4xjJycnJzMyc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\nPQsaaNeuXStWrHjrrbdCQ0NTU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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot workflow on huwiki on VE broken down by experience\n",
"\n",
"p <- reply_users_workflow_funnel_forplot_bywiki_experience %>%\n",
" filter(wiki == 'huwiki',\n",
" editor_interface == 'wikitext') %>%\n",
" group_by(step, experience_level, editor_interface) %>%\n",
" mutate(n_users = sum(n_users),\n",
" pct_users = n_users/init_users_experience) %>%\n",
" ggplot(aes(x=step, y= pct_users)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'red4') +\n",
" geom_text(aes(label = paste(round(pct_users * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'firstchange', y= 1.1, lab=c(\"total users: 18\",\"total users: 52\"),\n",
" experience_level = c(\"junior contributors (< 100 cumulative edits)\", \"senior contributors (> 500 cumulative edits)\")), vjust=1) +\n",
" facet_grid(~experience_level) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Step\",\n",
" title = \"Wikitext Reply Tool Workflow Funnel by Junior and Senior Contributors \\n on Hungarian Wikipedia \") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1),\n",
" legend.position = \"none\")\n",
" p\n",
" \n",
" \n",
"ggsave(\"Figures/wikitext_reply_workflow_huwiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A few key observations re the workflow completion rate for each wiki: \n",
"* For all threee opt-out wikis, senior contributors using visual editor typically had a higher rate of completion through each reply workflow step compared to wikitext. Results varies a little more for junior contributors. \n",
"* On Arabic Wikipedia, only 28% of junior contributors with 1 to 4 cumulative edits started typing a comment using visual editor after clicking the reply link. This is significantly lower compared to junior contributors with 1 to 4 edits using visual editor on the two other opt-out wikis (78% on Czech and 82% on Hungarian).\n",
"* On Hungarian Wikipedia, 33% of junior contributors with 1 to 4 cumulative edits using wikitext that clicked reply started typing a comment compated to 82% using visual editor. \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Reply Tool Completion Rate\n",
"\n",
"The section below focuses on the reply tool completion rate (Of of users who click the Reply link (action = `init`), what % of people successfully publish the comment they were drafting (action = `saveSuccess`))?\n",
"\n",
"We compared the reply tool completion rate to full-page talk page edit completion rate (grouped by experience level) to approximate how much more or less likely people are to successfully publish replies with the Reply Tool compared to full page wikitext editing. We excluded `section=new` edits from these comparison charts since we can be relatively sure that contributors are not using the `section=new` form and workflow for replying.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Reply Tool Completion Rate by Editor Experience"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"reply_users_workflow_funnel_forplot_overall <- inner_join(reply_users_workflow_funnel_clean, init_users_overall)"
]
},
{
"cell_type": "code",
"execution_count": 303,
"metadata": {},
"outputs": [],
"source": [
"reply_tool_completion_rate_overall <- reply_users_workflow_funnel_forplot_overall %>%\n",
" filter(step == 'savesuccess') %>%\n",
" group_by(edit_count_bucket) %>%\n",
" summarise(n_users = sum(n_users),\n",
" pct_replytool_completion_rate = sum(n_users)/init_users_overall, .groups = 'drop') %>%\n",
" distinct()"
]
},
{
"cell_type": "code",
"execution_count": 356,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot completion rate for reply tool by Editor Experience for both Interfaces\n",
"\n",
"p <- reply_tool_completion_rate_overall %>%\n",
" ggplot(aes(x=edit_count_bucket, y= pct_replytool_completion_rate)) +\n",
" geom_bar(stat='identity', position = 'dodge', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(pct_replytool_completion_rate * 100), '%')), vjust=-0.5) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent completion rate\",\n",
" x = \"Cumulative edit count\",\n",
" title = \"Reply Tool Completion Rate for both editing interfaces by editor experience \\n across all opt-out wikis\") +\n",
" theme_bw() +\n",
" scale_fill_brewer(palette=\"Set1\") +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position = 'bottom'\n",
" ) \n",
" \n",
"p\n",
"ggsave(\"Figures/reply_completion_rate_overall_editcount_bothinterfaces.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 306,
"metadata": {},
"outputs": [],
"source": [
"reply_tool_completion_rate_byeditcount <- reply_users_workflow_funnel_forplot_editcount %>%\n",
" filter(step == 'savesuccess') %>%\n",
" group_by(edit_count_bucket, editor_interface) %>%\n",
" summarise(n_users = sum(n_users),\n",
" pct_replytool_completion_rate = sum(n_users)/init_users_byeditcount, .groups = 'drop')\n"
]
},
{
"cell_type": "code",
"execution_count": 498,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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PNP9hm5qrZkS0hPT5fNKxQKbW1taYKF\nCxfKLf/NN9+kCZKSkhQVzmEz06Tlax4Y5epqnz9/Xm525kFCReUroslg0izmd63t27dLHWJ5\nSTX51pTTpJlpb8hivo5mSQVQmAZ2/PhxuSUXFxebmZnJzSvWOPjCVfM+fPiwkk9Rjk1gVNXu\no4NWyv70NQyMKumMo0aNoofWr1/PvkD0TUXQN6WofekYTON/9dVX+Xx+r1696H8XLFggN70m\nTUg33VkbNyqajHWGNggAgEHBqvQAYOiSk5O/+599+/b9+uuv9C1j5ubmb7zxxvnz552cnCTT\ni8Vi+rYye3t7Ja/78ff3b926NSFEydKu48aNk7u/devWgwcPJoSIRKKrV6+yOQsejzd37lxa\nvbi4OKmj+/fvpxtz5sxhU5oampqamIVZFb14nsfjMYcyMjI4yau2qqoqZpuJP6qEq2rb2dkN\nGDBAdr+JiQnz8ODIkSPl5mV+WSouLlZUT66aGYctXw1cXW1bW9uBAwfKPRQQEEA3nj17pl4l\nVR1MZJWUlNy8eTM9PT31f5hV7JnXlqlEZ9+aqs1M70OWFKaBmZmZMb/fSnF3d+/fv79WP51o\n1rxNTEyioqK0UUNKS92Hq1bK7emz74xCofDixYt0e9asWSzLR99kCX2TExs2bKDN7N69e926\ndaMn9eqrr37++efN5lWpCem3O3P16aqOdQY+CACA3iEwCgAvq6FDh8bGxsoGMp4+fVpWVkYI\nqaqq4ilFH9Z+/vy53PK9vLxcXFwUfXq3bt3oBvtoyOzZs+mMiYMHD4pEImY/XUWBEGJubj5z\n5kyWpanqyZMn9fX1hBAPDw8PDw9FyXr06EE3JNeE1SSv2iSXVqArKqiKq2r7+PgoWq6BedKt\nXbt2yhPU1tbKTcBhM+Oq5auHq6vdtm1bOs1EFtMk1GsPSigaTBj37t2bP3++u7u7h4dHSEhI\neHj40P9h3k/K5/PV+GjdfGvqNTNtD1nNvoxP8vFbpoF16tTJ2tq62XPhFofNmxkTtEFL3Yer\nVsrJ6avRGf/777/q6mpCiKurq6+vL8sPQt9E31SDSpdOkpmZWUJCAo2vPXnyhBBiZWV19OhR\nJZeUUrUJ6bc7c/jpKo11hjwIAIAhQGAUAAwdc5cpEomKi4v/+OMPuljt77//HhoayswQYdCb\nGPaYZ7WkODs7K8nF3IZWVFSw/CAPD4/Ro0cTQv79999z584x+5OSkmidR48e7ebmxrI0VTH1\nVHIDLXm0vLyck7xqk7z+dFqfqriqtpJfS3j/ezelojRMAsnfXSVx2My4avnq0eXVVnQxm6Xq\nYELt3r27e/fue/fuVT7Vjv5yrirdfGvqNTP9DllSmLqxPBctfbqGzdvBwYHbiknRUvfhqpVq\nfvrqdUam/io1V/RNltA3ueLr67tq1Srmvxs2bOjatWuzuVRtQvrtzlx9uqpjnSEPAgBgCMz0\nXQEAALZ4PJ67u7u7u3tkZGRMTMy3336bn58/derUtLQ0yb8bCwQCutGhQ4e9e/eyKVaNyojF\nYjVyzZ8/PykpiRCyf//+oUOH0p3Mg2/04ThtY3m+cpNpkldV9vb2Xl5ehYWFhJAbN24wl0sN\nuqw2t1RqZrpp+VwVq9+rzXIwIYScO3fu/fffJ4SYmJi8+eab48aNCwwMdHd3t7GxoSnv3Lmj\nyUwoQ/jWlDQzQxiyVKLeyMyehs1b0RQnA8dVK9Xw9DXvjCp1H/RNbqFvNovP53/zzTfMf5OT\nk5cvX67ogRWWZC+7fruz3rvVSzcIAIBuIDAKAC+lL774Ij09/d69exkZGd9+++17773HHGL+\neF5RUREeHq72Ryj/QzEz6cDR0ZF9mcOHD2/btu2TJ0+SkpLKy8udnJz+++8/uri5t7f38OHD\n1a5ts5jHhJU/6cMclTwvTfJqIjw8PCEhgRCSkpLCvE2fPX1VWyUcNjOuWr56XoqrLZeSwYQQ\nsm3bNroRFxfHLKUlSb0n6Bm6+dbUbmZ6HLKkMHVjeS7cenmbNyf0O7Yw1O6MTP1LSkrYfxz6\nJkvom1yZP38+fYiex+OJxeL09PStW7cyizIpomoT0m931tenG/IgAACGAI/SA8BLycLCIjY2\nlm5v2LCBvtyHatOmTatWrQghZWVld+/eVfsjCgsLldxnSy78yr5MExMTuh5CQ0MDfRFYXFwc\nfdhn9uzZWp2w4OPjQxcnLSoqUnJfyLw5vlOnTpzk1cT48ePpxoULF+7cuaNqdn1VWyUcNjOu\nWr56XoqrLZeSwUQsFtPlGtzc3GbMmCE3u4aXWjffmtrNTI9DlpS2bdvSBpabm6vkcUXmXLj1\n8jZvTuh3bKE06Yw+Pj70tYOlpaWPHz9m+Ynomyyhb3Ji3759x48fJ4R4eHicPn3a3NycELJh\nw4Zml15UtQnptzvr69MNeRAAAEOAwCgAvKxGjhzZt29fQkhZWZnkqp3m5ubM33W///57TT6C\nPqcmq7Ky8vz584QQHo9H68DeW2+9RX9jOXDggFgsPnjwIC3nrbfe0qSqzTI3N+/VqxfdTkxM\nlJtGLBYzh0JDQznJq4nXX3+duZWfN28e80yTcsz67/qqtqq4amYatnwLCwu6IRQKVc1LXp6r\nLZeiwaS6urqxsZEQ4uzsrOgROUUnS9hdUg7HK+XUbmb6GrKkmJub9+zZkxAiEAhOnz4tN01J\nSUlmZqaqJbP8ml7e5q2cQbVSJTTpjKampoMGDaLbtAGzgb7JEvqm5nJychYvXkwI4fF4hw4d\nGjly5ObNmwkhAoFg+vTpVVVVyrOr1IT025319ekGPggAgN4hMAoAL7F169bRjS+++ELyKS36\nGjJCyJ49e65cuaK8kKamJkWHtm7dKnf6w5YtW+jaDsOHD3d3d1epzm3atKHrvdy6dSs2NvbR\no0eEkMGDB/v5+alUjhqYNWq3bt0q9z77wIEDubm5hBAnJ6cxY8ZwlVdtJiYmO3fupL8DX7t2\nberUqcpfbF9fX79kyRKmVeir2qrisJlp0vJNTEzoCrOqrjbAeCmutiJyB5NWrVrRuENeXh5d\n0FbKb7/9JrnyiRSWl5Sr8Uo5tZuZHocsKcw8wU2bNsm9Dhs2bGD55xNJLL+ml7p5K2FQrVQJ\nDTtjTEwM3YiNjX3w4AHLD0XfZAl9UxONjY3Tpk2rra0lhCxZsmTYsGGEkOXLl0dGRhJCHj16\n9M477ygvQdUmpN/urK9PN+RBAAD0TwwAYJD8/f3pMMUsJC0XnadACFm1apXkfrpgKyHE3t4+\nISFBJBJJZayvr09KSgoPD09KSpLcX1RUJDlIvvbaa3w+XzLBN998Q0N1PB7v0qVLUsXS39y8\nvb2V1PnkyZO0cDOz//+i54SEBCXpVdK9e3da5o8//ih1qK6urmPHjvRoWFhYcXGx5NHExERL\nS0t6dNu2bRzmFbO7LIps3LiR+To6dep0+PDhFy9eSKUpKCjYsWOHp6cnIWTOnDmcVJtpCSEh\nIYrqxsw9efTokdwEO3fupAk+++wzuYVz3szUbvlisZiZd3P9+nVFp6zk07V9tU+cOEHTLFq0\nSEn1ZGkymDBf8bRp0xoaGiTTJyUl2draMl/iqFGjZMtkeUk1+daU0LCZMbgdslh+HbJqa2vb\ntWtH806ePLmmpoY5JBKJtm/fLnmy3377rVR2Jb2Gzdek7ebNhqJLp2H30XYrZX/6zOsU4+Li\nZI9q2BlpvIkQ4uHhkZqaKnVUJBKlpaUdPHiQq7NWDn1TUgvum2x88MEHNG9wcLBkwy4sLGTW\nlP/hhx8U1Vy9JqSD7qyNGxUNxzqDGgQAwKBg8SUAeLmtXbt23LhxhJBdu3Z98MEHrq6udH98\nfHx4ePitW7eqqqqmT5++du3aIUOG+Pj4mJiYlJWV/f3339euXaMzCxYtWiS35KCgIHt7+99/\n/71Tp04TJ05s3759ZWVlcnJydnY2TbB06dIBAwaoUedRo0bR9dbpBApHR0fmZZpaZWVllZCQ\nEB4eXltbe+nSpU6dOo0ZM6Zz584vXrxIS0tj/hI+bNiw5cuXc5hXQ+vWrbO2tl65cqVQKMzN\nzY2Ojra0tAwJCfH09GzVqlVZWdmjR4/u3bvHpHdwcDCEarPEeTPTpOVHRUVlZWURQkaNGhUd\nHd2uXTv6y7aHh8fEiROb/WjDv9rKyR1MVqxYQWcYHTly5MqVK2PHjvXx8amoqDh37hx99duq\nVau2bt2qqEyWl1Tz8Uo5DZuZloasbdu2NftI486dO318fOi2jY1NXFzc8OHDm5qajh07lpGR\nMWHCBF9f37KystOnT9++fdvOzm7SpEkHDhxQtSZsvqaXvXkrYSCttFkadsbDhw+Hhobm5uYW\nFxdHRkYGBwcPGjTIzc2tvr4+Ly8vPT29oKBgzpw5zPRD3Zw1+qZyL13fVPXSnT179osvviCE\n2NjYHDlyhHl7ACHE09PzwIEDtM2/++67/fv3Z8KvktRrQvrtzvr6dMMcBADAIOg7MgsAIB/L\nP7+LRKKgoCCactmyZZKHamtr582bp3wJAhcXl6tXr0rmkvxzdFFRUZ8+fWRz8Xi8xYsXy/7R\nWMx6aqTkMqPvv/8+66vSPCUzRqmsrCwlz9nNmjWrvr5eUeFq59Vkxih18eLFsLAwJV8lIaRd\nu3b79++X/V7Uq7ZuZoxqo5mp1/LFYnFlZWVAQIBs4j59+rD/dO1dbW3PGFU0mGzevFnuOw0t\nLCy++uorZlkwuZPUWF5SsQbfmhIaNjNJHA5Zcn+3V+TOnTtS2U+ePNm6dWvZlE5OTikpKUxc\nTKVZaey/Ju01bza0NGNU262UqxmjYs06o1gsLi8vV/4k9YIFC2RzoW/Khb4pSb1LV1JSwjzh\nvnfvXrklM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hw+sMWUlJyUknnbRgwYLMzMzC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\nZpndXK/5/2Fe/dN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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot completion rate for reply tool by Editor Experience\n",
"\n",
"p <- reply_tool_completion_rate_byeditcount %>%\n",
" ggplot(aes(x=editor_interface, y= pct_replytool_completion_rate)) +\n",
" geom_bar(aes(fill = editor_interface),stat='identity', position = 'dodge') +\n",
" geom_text(aes(label = paste(round(pct_replytool_completion_rate * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'visualeditor', y= 1.1, lab=c(\"total users: 18\",\"total users: 108\",\"total users: 132\", \"total users: 57\", \"total users: 154\"),\n",
" edit_count_bucket= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\" )), vjust=1) +\n",
" facet_grid(~edit_count_bucket) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent completion rate\",\n",
" x = \"Editor Interface\",\n",
" title = \"Reply Tool Completion Rate by Editor Interface by Editor Experience \\n Across All Opt-Out Wikis\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = c ('darkblue', 'red4')) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position = 'bottom',\n",
" axis.title.x = element_blank(),\n",
" axis.text.x=element_blank()\n",
" ) \n",
" \n",
"p\n",
"ggsave(\"Figures/reply_completion_rate_overall_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 308,
"metadata": {},
"outputs": [],
"source": [
"reply_tool_completion_rate_byexperience <- reply_users_workflow_funnel_forplot_experience %>%\n",
" filter(step == 'savesuccess') %>%\n",
" group_by(experience_level, editor_interface) %>%\n",
" summarise(pct_replytool_completion_rate = sum(n_users/init_users_byexperience), .groups = 'drop')"
]
},
{
"cell_type": "code",
"execution_count": 499,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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tG1ANGSnZ29ZcuW6tWrp6WlVXQtsGuLFi3q379/nTp1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PKOO+5IaIccXiTy6+PdAnD8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\nN9+86qqryo/v27fvu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rCwcN26de+///6YMWNOOumkoqKi9Mp7NpBq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\nBKMAAAAAQHD+H9XF3DnVzs+5AAAAAElFTkSuQmCC",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot completion rate for reply tool by Junior vs Senior Contributors\n",
"\n",
"p <- reply_tool_completion_rate_byexperience %>%\n",
" ggplot(aes(x=editor_interface, y= pct_replytool_completion_rate)) +\n",
" geom_bar(aes(fill = editor_interface),stat='identity', position = 'dodge') +\n",
" geom_text(aes(label = paste(round(pct_replytool_completion_rate * 100), '%')), vjust=-0.5) +\n",
" geom_text(aes(x,y,label=lab),\n",
" data=data.frame(x= 'visualeditor', y= 1.1, lab=c(\"total users: 258\",\"total users: 171\"),\n",
" experience_level = c(\"junior contributors (< 100 cumulative edits)\", \"senior contributors (> 500 cumulative edits)\")), vjust=1) +\n",
" facet_grid(~experience_level) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent completion rate\",\n",
" x = \"Editor Interface\",\n",
" title = \"Reply Tool Completion Rate by Editor Interface for Junior and Senior Contributors \\n Across All Opt-Out Wikis\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = c ('darkblue', 'red4')) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position = 'bottom',\n",
" axis.title.x = element_blank(),\n",
" axis.text.x=element_blank()\n",
" ) \n",
" \n",
"p\n",
"ggsave(\"Figures/reply_completion_rate_overall_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Reply comments made with Visual Editor had a higher completion rate across all contributor experience levels. The completion rate generally increases with experience level. There is a slightly higher completion rate for first time contributors (0 cumulative edits) than contributors with 1 to 4 edits; however, available data for the 0 edits group was limited (only 18 users across all three opt-out wikis) at the time of analysis and not large enough to draw any conclusions about this user group.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Reply Tool vs Full Talk Page Wikitext Completion Rates"
]
},
{
"cell_type": "code",
"execution_count": 314,
"metadata": {},
"outputs": [],
"source": [
"# collect data on talk page wikitext edit completion rate\n",
"query <- \n",
"\"\n",
"--only include full sessions where an init talk page edit was logged during the reviewed timeframe \n",
" \n",
"WITH init_sessions AS (\n",
"SELECT \n",
" event.editing_session_id AS session_id,\n",
" wiki AS wiki\n",
"FROM event_sanitized.editattemptstep\n",
"WHERE\n",
" year = 2020 AND\n",
" event.action = 'init'\n",
"-- remove all 'section = new' events\n",
" AND NOT (event.init_type = 'section' and event.init_mechanism = 'new')\n",
" AND dt between '2020-09-24' AND '2020-12-08'\n",
"-- review wikis where deployed as opt-out\n",
" AND wiki IN ('arwiki', 'cswiki', 'huwiki')\n",
" AND event.integration= 'page'\n",
"-- only review talk pages\n",
" AND event.page_ns % 2 == 1 \n",
"-- remove anonymous users\n",
" AND event.user_id != 0\n",
")\n",
"SELECT\n",
"user,\n",
"wiki,\n",
"min(edit_count) AS edit_count,\n",
"sum(cast(action = 'init' as int)) >= 1 AS init_completed,\n",
"sum(cast(action = 'saveSuccess' as int)) >= 1 AS saveSuccess_completed\n",
"FROM (\n",
"SELECT\n",
" eas.event.user_editcount AS edit_count,\n",
" eas.event.user_id AS user,\n",
" eas.event.editing_session_id AS session_id,\n",
" eas.event.action AS action,\n",
" eas.wiki AS wiki,\n",
" COUNT(*) AS events\n",
"FROM event_sanitized.editattemptstep eas\n",
"INNER JOIN\n",
" init_sessions \n",
" ON eas.event.editing_session_id = init_sessions.session_id \n",
" AND eas.wiki = init_sessions.wiki\n",
"WHERE\n",
" year = 2020 \n",
"-- events since deployment date\n",
" AND dt between '2020-09-24' AND '2020-12-08'\n",
"-- review wikis where deployed as opt-out\n",
" AND eas.wiki IN ('arwiki', 'cswiki', 'huwiki')\n",
" AND NOT (event.init_type = 'section' and event.init_mechanism = 'new')\n",
" AND eas.event.integration= 'page'\n",
"-- only review talk pages\n",
" AND eas.event.page_ns % 2 == 1 \n",
"-- remove anonymous users\n",
" AND eas.event.user_id != 0\n",
"GROUP BY \n",
" eas.event.user_id,\n",
" eas.event.user_editcount,\n",
" eas.event.action,\n",
" eas.event.editing_session_id,\n",
" eas.wiki\n",
") AS sessions_data\n",
"GROUP BY\n",
"user,\n",
"wiki\n",
"\"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"collect_full_talk_page_edits <- wmfdata::query_hive(query)"
]
},
{
"cell_type": "code",
"execution_count": 316,
"metadata": {},
"outputs": [],
"source": [
"# add column with user edit count buckets\n",
"\n",
"full_talk_page_events_with_editcount <- collect_full_talk_page_edits %>%\n",
" mutate(edit_count_bucket = case_when(\n",
" edit_count == 0 ~ '0 edits',\n",
" edit_count >=1 & edit_count <= 4 ~ '1-4 edits',\n",
" edit_count >=5 & edit_count <= 99 ~ '5-99 edits',\n",
" edit_count >=100 & edit_count <= 999 ~ '100-999 edits',\n",
" edit_count >=1000 ~ '1000+ edits'),\n",
" experience_level = case_when( \n",
" edit_count < 100 ~ 'junior contributors (< 100 cumulative edits)',\n",
" edit_count > 500 ~ 'senior contributors (> 500 cumulative edits)'))"
]
},
{
"cell_type": "code",
"execution_count": 317,
"metadata": {},
"outputs": [],
"source": [
"# Order edit counts\n",
"full_talk_page_events_with_editcount$edit_count_bucket %<>% \n",
" factor(levels= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\"))"
]
},
{
"cell_type": "code",
"execution_count": 318,
"metadata": {},
"outputs": [],
"source": [
"# completion rate by editcount\n",
"full_talk_users_completion_rate_editcount <- full_talk_page_events_with_editcount %>%\n",
" group_by(edit_count_bucket) %>%\n",
" summarise(init = sum(init_completed == 'true'),\n",
" savesuccess = sum(savesuccess_completed == 'true'),\n",
" full_page_wikitext = savesuccess/init, .groups = 'drop') %>%\n",
"# remove unneed columns to match reply tool table for joining later\n",
" select(-c(2,3))"
]
},
{
"cell_type": "code",
"execution_count": 319,
"metadata": {},
"outputs": [],
"source": [
"# completion rate by senior vs junior contributors\n",
"full_talk_users_completion_rate_experience <- full_talk_page_events_with_editcount %>%\n",
" filter(experience_level != 'NA') %>%\n",
" group_by(experience_level) %>%\n",
" summarise(init = sum(init_completed == 'true'),\n",
" savesuccess = sum(savesuccess_completed == 'true'),\n",
" full_page_wikitext = savesuccess/init, .groups = 'drop') %>%\n",
"# remove unneed columns to match reply tool table for joining later\n",
" select(-c(2,3))\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Reply Tool (Wikitext and VE) vs Full Page Wikitext"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join to show comparison between the two groups by edit count\n",
"edit_completion_rate_comparison_both <- inner_join(full_talk_users_completion_rate_editcount, reply_tool_completion_rate_overall) %>%\n",
" rename(reply_tool_both_interfaces = pct_replytool_completion_rate) %>%\n",
" select(-3) # remove uneeded column\n"
]
},
{
"cell_type": "code",
"execution_count": 472,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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NnHv16hVCePvtt08b4a233goh9OzZ81y/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\ndejQYez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KAsAObunSpVEvm0QiMWjQoLff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\nAElFTkSuQmCC",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot comparison between full page and reply tool completion rates for both editing interfaces\n",
"\n",
"p <- edit_completion_rate_comparison_both %>%\n",
" gather(\"edit_type\", \"completion_rate\", 2:3) %>%\n",
" ggplot(aes(x=edit_type, y= completion_rate, fill = edit_type)) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" facet_grid(~edit_count_bucket) +\n",
" geom_text(aes(label = paste(round(completion_rate * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent completion rate\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Reply Tool (VE and Wikitext) vs Full Page Wikitext Completion Rate by Editor Experience\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = c('red4', 'darkblue'), labels = c('Full Page Wikitext', 'Reply Tool (VE and Wikitext)')) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position=\"bottom\",\n",
" axis.title.x=element_blank(),\n",
" axis.text.x=element_blank(),\n",
" axis.ticks.x=element_blank())\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_completion_rate_wikitext_comparison_both.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 322,
"metadata": {},
"outputs": [],
"source": [
"reply_tool_completion_rate_byexperience_both_interfaces <- reply_users_workflow_funnel_forplot_experience_both %>%\n",
" filter(step == 'savesuccess') %>%\n",
" group_by(experience_level) %>%\n",
" summarise(pct_replytool_completion_rate = sum(n_users/init_users_byexperience_both), .groups = 'drop')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join to show comparison between the two groups by edit count\n",
"edit_completion_rate_comparison_both_interfaces <- inner_join(full_talk_users_completion_rate_experience, reply_tool_completion_rate_byexperience_both_interfaces) %>%\n",
" rename(reply_tool_both_interfaces_byexperience = pct_replytool_completion_rate) \n"
]
},
{
"cell_type": "code",
"execution_count": 473,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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NAci5puAAAAAAAAAABUN4JRAAAAAAAAAJpDMAoAAAAAAABAcwhGAQAAAAAAAGgOwSgA\nAAAAAAAAzSEYBQAAAAAAAKA5BKMAAAAAAAAANIdgFAAAAAAAAIDmEIwCAAAAAAAA0ByCUQAA\nAAAAAACaQzAKAAAAAAAAQHMIRgEAAAAAAABoDsEoAAAAAAAAAM0hGAUAAAAAAACgOQSjAAAA\nAAAAADSHYBQAAAAAAACA5vwfxDm+1VNo3+wAAAAASUVORK5CYII=",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot comparison between full page and reply tool completion rates for both editing interfaces\n",
"\n",
"p <- edit_completion_rate_comparison_both_interfaces %>%\n",
" gather(\"edit_type\", \"completion_rate\", 2:3) %>%\n",
" ggplot(aes(x=edit_type, y= completion_rate, fill = edit_type)) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" facet_wrap(~experience_level) +\n",
" geom_text(aes(label = paste(round(completion_rate * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent completion rate\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Reply Tool (VE and Wikitext) vs Full Page Wikitext Completion Rate for Junior and Senior Contributors\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = c('red4', 'darkblue'), labels = c('Full Page Wikitext', 'Reply Tool (VE and Wikitext)')) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position=\"bottom\",\n",
" axis.title.x=element_blank(),\n",
" axis.text.x=element_blank(),\n",
" axis.ticks.x=element_blank())\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_completion_rate_comparison_both_junior_senior.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Reply Tool Visual Editor vs Full Page Wikitext"
]
},
{
"cell_type": "code",
"execution_count": 474,
"metadata": {},
"outputs": [],
"source": [
"# reply tool visual editor completion rate\n",
"reply_tool_completion_rate_ve <- reply_tool_completion_rate_byeditcount %>%\n",
" filter(editor_interface == 'visualeditor') %>%\n",
" rename(reply_tool_visualeditor = pct_replytool_completion_rate) %>%\n",
" select(-c(2,3)) %>%\n",
" distinct()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join to show comparison between the two groups by edit count\n",
"edit_completion_rate_comparison_ve <- inner_join(full_talk_users_completion_rate_editcount, reply_tool_completion_rate_ve)\n"
]
},
{
"cell_type": "code",
"execution_count": 476,
"metadata": {},
"outputs": [
{
"data": {
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On8YD/9xSU1paWlpamg98TEVFRXl5eVZWVnp6+tHuBUKo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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
" # plot comparison between full page and reply tool ve completion rates\n",
"\n",
"p <- edit_completion_rate_comparison_ve %>%\n",
" gather(\"edit_type\", \"completion_rate\", 2:3) %>%\n",
" ggplot(aes(x=edit_type, y= completion_rate, fill = edit_type)) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" facet_grid(~ edit_count_bucket) +\n",
" geom_text(aes(label = paste(round(completion_rate * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent completion rate\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Reply Tool Visual Editor vs Full Talk Page Wikitext Completion Rate by Editor Experience\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = c('red4', 'darkblue'), labels = c('Full Page Wikitext', 'Reply Tool Visual Editor')) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position=\"bottom\",\n",
" axis.title.x=element_blank(),\n",
" axis.text.x=element_blank(),\n",
" axis.ticks.x=element_blank())\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_completion_rate_wikitext_comparison_ve.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 478,
"metadata": {},
"outputs": [],
"source": [
"# reply tool VE completion rate - junior vs senior contributors\n",
"reply_tool_completion_rate_ve_junior_senior <- reply_tool_completion_rate_byexperience %>%\n",
" filter(editor_interface == 'visualeditor') %>%\n",
" rename(reply_tool_visualeditor = pct_replytool_completion_rate) %>%\n",
" select(-2) \n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join to show comparison between the two groups by junior and senior contributor groups\n",
"edit_completion_rate_comparison_ve_junior_senior <- inner_join(full_talk_users_completion_rate_experience, reply_tool_completion_rate_ve_junior_senior)\n"
]
},
{
"cell_type": "code",
"execution_count": 481,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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VChQq9evYIgePHFF/PO/BgEwaJFi6ZOnRoE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\naWGv3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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot comparison between full page and reply tool completion rates for junior and senior contributors\n",
"\n",
"p <- edit_completion_rate_comparison_ve_junior_senior %>%\n",
" gather(\"edit_type\", \"completion_rate\", 2:3) %>%\n",
" ggplot(aes(x=edit_type, y= completion_rate, fill = edit_type)) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" facet_grid(~experience_level) +\n",
" geom_text(aes(label = paste(round(completion_rate * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent completion rate\",\n",
" x = \"Experience level\",\n",
" title = \"Reply Tool Visual Editor vs Full Page Wikitext Completion Rate \\n for Junior and Senior Contributors\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = c('red4', 'darkblue'), labels = c('Full Page Wikitext', 'Reply Tool Visual Editor')) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position=\"bottom\",\n",
" axis.title.x=element_blank(),\n",
" axis.text.x=element_blank(),\n",
" axis.ticks.x=element_blank())\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_completion_rate_ve_comparison_junior_senior.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Reply Tool Wikitext vs Full Page Wikitext"
]
},
{
"cell_type": "code",
"execution_count": 347,
"metadata": {},
"outputs": [],
"source": [
"# reply tool wikitext completion rate\n",
"reply_tool_completion_rate_wikitext <- reply_tool_completion_rate_byeditcount %>%\n",
" filter(editor_interface == 'wikitext') %>%\n",
" rename(reply_tool_wikitext = pct_replytool_completion_rate) %>%\n",
" select(-c(2,3)) %>%\n",
" distinct()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join to show comparison between the two groups by edit count\n",
"edit_completion_rate_comparison_wikitext <- inner_join(full_talk_users_completion_rate_editcount, reply_tool_completion_rate_wikitext)\n"
]
},
{
"cell_type": "code",
"execution_count": 500,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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LmyevXqxVQ48cQTHa6Ik6cc0ImFrV27tvgK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\nSUVORK5CYII=",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot comparison between full page and reply tool completion rates\n",
"\n",
"p <- edit_completion_rate_comparison_wikitext %>%\n",
" gather(\"edit_type\", \"completion_rate\", 2:3) %>%\n",
" ggplot(aes(x=edit_type, y= completion_rate, fill = edit_type)) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" facet_grid(~edit_count_bucket) +\n",
" geom_text(aes(label = paste(round(completion_rate * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent completion rate\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Reply Tool Wikitext vs Full Page Wikitext Completion Rate by Editor Experience\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = c('red4', 'darkblue'), labels = c('Full Page Wikitext', 'Reply Tool Wikitext')) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position=\"bottom\",\n",
" axis.title.x=element_blank(),\n",
" axis.text.x=element_blank(),\n",
" axis.ticks.x=element_blank())\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_completion_rate_wikitext_comparison_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 351,
"metadata": {},
"outputs": [],
"source": [
"# reply tool wikitext completion rate - junior vs senior contributors\n",
"reply_tool_completion_rate_wikitext_junior_senior <- reply_tool_completion_rate_byexperience %>%\n",
" filter(editor_interface == 'wikitext') %>%\n",
" rename(reply_tool_wikitext = pct_replytool_completion_rate) %>%\n",
" select(-2) \n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join to show comparison between the two groups by junior and senior contributor groups\n",
"edit_completion_rate_comparison_wikitext_junior_senior <- inner_join(full_talk_users_completion_rate_experience, reply_tool_completion_rate_wikitext_junior_senior)\n"
]
},
{
"cell_type": "code",
"execution_count": 484,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot comparison between full page and reply tool completion rates for junior and senior contributors\n",
"\n",
"p <- edit_completion_rate_comparison_wikitext_junior_senior %>%\n",
" gather(\"edit_type\", \"completion_rate\", 2:3) %>%\n",
" ggplot(aes(x=edit_type, y= completion_rate, fill = edit_type)) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" facet_grid(~ experience_level) +\n",
" geom_text(aes(label = paste(round(completion_rate * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent completion rate\",\n",
" x = \"Experience level\",\n",
" title = \"Reply Tool Wikitext vs Full Page Wikitext Completion Rate \\n for Junior and Senior Contributors\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = c('red4', 'darkblue'), labels = c('Full Page Wikitext', 'Reply Tool Wikitext')) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position=\"bottom\",\n",
" axis.title.x=element_blank(),\n",
" axis.text.x=element_blank(),\n",
" axis.ticks.x=element_blank())\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_completion_rate_wikitext_comparison_junior_senior.png.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Reply tool comments overall had significantly higher completion rates compared to full talk page wikitext edits for junior contributors (62% vs 15%). Junior contributors had a lower edit completion rate with the reply tool using wikitext (56%) compared to visual editor (64%).\n",
"\n",
"Completion rates are much more similar for senior contributors. Senior contributors with over 500 cumulative edits had 80% completion rate when making full page wikitext edits compared a completion rate of 75% when using the reply tool. Senior contributors have a higher completion rate using wikitext on full page edits compared to reply tool edits while they have a slighty higher completion rate using VE on reply tool edits compared to full page edits."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 2. Are people satisfied with the feature?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## People who publish at least one comment and turn off the Reply Tool preference (name: Enable quick replying) in Special:Preferences."
]
},
{
"cell_type": "code",
"execution_count": 359,
"metadata": {},
"outputs": [],
"source": [
"query <- \"\n",
"--find users that opt out of the reply tool preference \n",
"WITH opt_out_users AS (\n",
"SELECT\n",
" event.userid as opt_out_user,\n",
" wiki as opt_out_wiki,\n",
" min(event.saveTimestamp) as opt_out_time,\n",
" sum(cast(event.value = '\\\"0\\\"' as int)) as opt_outs\n",
"FROM \n",
" event.prefupdate\n",
"WHERE\n",
" event.property = 'discussiontools-betaenable' AND\n",
" wiki IN ('arwiki', 'cswiki', 'huwiki') AND\n",
" event.value = '\\\"0\\\"' AND\n",
" CONCAT(year, '-', LPAD(month, 2, '0'), '-', LPAD(day, 2, '0')) >= '2020-09-24' AND\n",
" CONCAT(year, '-', LPAD(month, 2, '0'), '-', LPAD(day, 2, '0')) < '2020-12-01'\n",
"GROUP BY \n",
" event.userid, \n",
" wiki\n",
"),\n",
"-- find users that made at least one edit with the reply tool\n",
"reply_users AS (\n",
"SELECT\n",
" event_user_id as reply_user,\n",
" wiki_db as reply_wiki,\n",
" min(mh.event_timestamp) as first_reply_time\n",
"FROM wmf.mediawiki_history AS mh\n",
"WHERE \n",
" ARRAY_CONTAINS(revision_tags, 'discussiontools') AND\n",
" snapshot = '2020-12' AND\n",
" event_timestamp >= '2020-09-24' AND \n",
" event_timestamp <= '2020-12-08' AND\n",
" wiki_db IN ('arwiki','cswiki', 'huwiki') AND \n",
" SIZE(event_user_is_bot_by_historical) = 0 AND\n",
" SIZE(event_user_is_bot_by) = 0 AND\n",
" event_entity = 'revision' AND \n",
" event_type = 'create' AND\n",
" event_user_id IS NOT NULL\n",
"GROUP BY\n",
" event_user_id,\n",
" wiki_db\n",
")\n",
"\n",
"-- Main Query --\n",
"SELECT\n",
" reply_wiki AS wiki,\n",
" opt_out_time,\n",
" SUM(CAST(opt_out_user IS NOT NULL and first_reply_time < opt_out_time AS int)) AS opt_out_users,\n",
" COUNT(*) AS all_reply_tool_users\n",
"\n",
"FROM (\n",
"SELECT\n",
" reply_users.reply_user,\n",
" reply_users.reply_wiki,\n",
" reply_users.first_reply_time,\n",
" opt_out_users.opt_out_time,\n",
" opt_out_users.opt_out_wiki,\n",
" opt_out_users.opt_out_user\n",
"FROM reply_users\n",
"LEFT JOIN opt_out_users ON \n",
" reply_users.reply_user = opt_out_users.opt_out_user AND\n",
" reply_users.reply_wiki = opt_out_users.opt_out_wiki \n",
"WHERE \n",
"--limit to users that opt'd out and stayed opt'd out\n",
" opt_out_users.opt_outs = 1 \n",
") sessions\n",
"GROUP BY\n",
" sessions.reply_wiki,\n",
" sessions.opt_out_time\n",
"\"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"opt_out_after_reply <- wmfdata::query_hive(query)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"According to data available in [PrefUpdate](https://meta.wikimedia.org/wiki/Schema:PrefUpdate), there has only been one user across all three op-out wikis (on Hungarian Wikipedia) that has turned off the Reply Tool preference in Special:Preferences after making a comment using the reply tool during the reviewed time period (24 September 2020 through 08 December 2020)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Distribution of reply tool users by number of comments posted"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We reviewed the distribution of reply tool users by the number of comments posted. We looked at users that made just 1 comment and those that made comments within identified buckets (e.g. \" E.g. \"1-5 edits,\" \"6-10 edits,\" etc.)\n",
"\n",
"- Data comes from [mediawiki_history](https://wikitech.wikimedia.org/wiki/Analytics/Data_Lake/Edits/MediaWiki_history) using the change tag implemented in [T242184](https://phabricator.wikimedia.org/T242184). \n",
"- We reviewed all edits made with the discussiontools tag. These include all users who were able to successfully make an edit using the reply tool. It does not include attempts with the tool that were not saved. \n",
"- Any self-identified bots were filtered out from the data; however, some un-identified bots might still be included."
]
},
{
"cell_type": "code",
"execution_count": 362,
"metadata": {},
"outputs": [],
"source": [
"# Collect users max reply edits during opt-out time\n",
"\n",
"query <- \"\n",
"\n",
"SELECT\n",
" wiki,\n",
" reply_user,\n",
" min(edit_count_bucket) AS edit_count_bucket,\n",
" min(experience_level) AS experience_level,\n",
" max(reply_edits) AS reply_edit_count\n",
"FROM (\n",
" SELECT\n",
" wiki_db AS wiki,\n",
" event_user_id as reply_user,\n",
" CASE\n",
" WHEN min(event_user_revision_count) is NULL THEN 'undefined'\n",
" WHEN min(event_user_revision_count) = 0 THEN '0 edits'\n",
" WHEN (min(event_user_revision_count) >=1 AND min(event_user_revision_count) < 5) THEN '1-4 edits'\n",
" WHEN (min(event_user_revision_count) >=5 AND min(event_user_revision_count) < 100) THEN '5-99 edits'\n",
" WHEN (min(event_user_revision_count) >=100 AND min(event_user_revision_count) < 1000) THEN '100-999 edits'\n",
" ELSE '1000+ edits'\n",
" END AS edit_count_bucket,\n",
" CASE\n",
" WHEN min(event_user_revision_count) < 100 THEN 'junior contributors (< 100 cumulative edits)' \n",
" WHEN min(event_user_revision_count) > 500 THEN 'senior contributors (> 500 cumulative edits)'\n",
" ELSE 'NA'\n",
" END AS experience_level,\n",
" max(size(event_user_is_bot_by) > 0 or size(event_user_is_bot_by_historical) > 0) as bot_by_group,\n",
" Count(*) as reply_edits\n",
"FROM wmf.mediawiki_history\n",
"WHERE \n",
" ARRAY_CONTAINS(revision_tags, 'discussiontools') AND\n",
" snapshot = '2020-12' AND\n",
" event_timestamp >= '2020-09-24' AND\n",
" event_timestamp <= '2020-12-08' AND\n",
" wiki_db IN ('arwiki','cswiki', 'huwiki') AND\n",
" event_entity = 'revision' AND\n",
" event_type = 'create' AND\n",
"-- remove anonymous users\n",
" event_user_id IS NOT NULL\n",
"GROUP BY\n",
" wiki_db,\n",
" event_user_id \n",
") edits\n",
"WHERE not bot_by_group\n",
"GROUP BY \n",
" reply_user, \n",
" wiki\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"collect_reply_tool_users <- wmfdata::query_hive(query)"
]
},
{
"cell_type": "code",
"execution_count": 364,
"metadata": {},
"outputs": [],
"source": [
"# Order edit counts\n",
"collect_reply_tool_users$edit_count_bucket %<>% \n",
" factor(levels= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\"))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Percent of users that made only 1 comment with the reply tool by Wiki"
]
},
{
"cell_type": "code",
"execution_count": 501,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"A tibble: 3 × 2\n",
"\n",
"\t| wiki | percent_users_1comments |
|---|
\n",
"\t| <chr> | <dbl> |
|---|
\n",
"\n",
"\n",
"\t| arwiki | 55.58583 |
\n",
"\t| cswiki | 51.74825 |
\n",
"\t| huwiki | 47.71242 |
\n",
"\n",
"
\n"
],
"text/latex": [
"A tibble: 3 × 2\n",
"\\begin{tabular}{ll}\n",
" wiki & percent\\_users\\_1comments\\\\\n",
" & \\\\\n",
"\\hline\n",
"\t arwiki & 55.58583\\\\\n",
"\t cswiki & 51.74825\\\\\n",
"\t huwiki & 47.71242\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A tibble: 3 × 2\n",
"\n",
"| wiki <chr> | percent_users_1comments <dbl> |\n",
"|---|---|\n",
"| arwiki | 55.58583 |\n",
"| cswiki | 51.74825 |\n",
"| huwiki | 47.71242 |\n",
"\n"
],
"text/plain": [
" wiki percent_users_1comments\n",
"1 arwiki 55.58583 \n",
"2 cswiki 51.74825 \n",
"3 huwiki 47.71242 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Find overall percent of users that made only 1 edit\n",
"reply_edits_overall_1edit <- collect_reply_tool_users %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_wiki_user_count = n()) %>%\n",
" filter(reply_edit_count == 1) %>%\n",
" group_by(wiki) %>%\n",
" summarise(percent_users_1comments = n()/total_wiki_user_count *100, .groups = 'drop') %>%\n",
" distinct()\n",
"\n",
"reply_edits_overall_1edit"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Roughly half of all reply tool users only made 1 comment using the reply tool on each of the opt-out wikis during the reviewed time period (24 September 2020 through 08 December 2020). Arabic Wipedia had the highest percent of users that only made 1 comment (55.6%) while Czech Wikipedia had the lowest (47.7%)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Percent of users that made only 1 edit with the reply tool by Wiki and Experience Level"
]
},
{
"cell_type": "code",
"execution_count": 366,
"metadata": {},
"outputs": [],
"source": [
"# Find overall number of users that made only 1 edit by edit count\n",
"reply_edits_1edit_bywiki_editcount <- collect_reply_tool_users %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_wiki_user_count = n()) %>%\n",
" filter(reply_edit_count == 1) %>%\n",
" group_by(wiki, edit_count_bucket) %>%\n",
" summarise(percent_users = n()/total_wiki_user_count, .groups = 'drop') %>%\n",
" distinct()\n"
]
},
{
"cell_type": "code",
"execution_count": 506,
"metadata": {},
"outputs": [],
"source": [
"# set plot colors\n",
"cbp1 <- c(\"#999999\", \"#E69F00\", \"#56B4E9\")"
]
},
{
"cell_type": "code",
"execution_count": 507,
"metadata": {},
"outputs": [
{
"data": {
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Ofnb9myZfbs2dUX2peVlR3r+Ut33nlnZWVl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\np0+f6pcLFiyIx+Pjxo0LIbz99tt5eXlDhw4dNGhQQUHBCy+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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot 1 edit completion rates by editor experience\n",
"\n",
"p <- reply_edits_1edit_bywiki_editcount %>%\n",
" ggplot(aes(x=wiki, y= percent_users, fill = wiki)) +\n",
" facet_wrap(~edit_count_bucket) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" geom_text(aes(label = paste(round(percent_users * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of users\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Percent of users that posted only 1 comment with the reply tool \\n by editor experience across all opt-out wikis\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = cbp1) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position=\"bottom\",\n",
" axis.title.x=element_blank(),\n",
" axis.text.x=element_blank(),\n",
" axis.ticks.x=element_blank())\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/one_comment_users_overall_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 368,
"metadata": {},
"outputs": [],
"source": [
"# Find overall number of users that made only 1 edit by junior and senior contributors\n",
"reply_edits_1edit_bywiki_experience <- collect_reply_tool_users %>%\n",
" group_by(wiki) %>%\n",
" filter(experience_level != 'NA') %>%\n",
" mutate(total_wiki_user_count = n()) %>%\n",
" filter(reply_edit_count == 1) %>%\n",
" group_by(wiki, experience_level) %>%\n",
" summarise(percent_users = n()/total_wiki_user_count, .groups = 'drop') %>%\n",
" distinct()\n"
]
},
{
"cell_type": "code",
"execution_count": 508,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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5c0MIhxxyyLXXXhtCyM/P//DDD+++++70QvuysvTtxEQAACAASURBVLKd3X/p8ssv\nT7/W2dnZ2dnZW7Zsqc3rAIQQHC+Q5nCAtD18OBQVFdWwt6qqKpFIOEL3PalzGgAfcZBWXFxc\nXFxc36OgbiQSiZor1Fsweuutt4YQSkpKPv744+eee+7BBx985513br755tTFRtO+8vfbmhfR\n70bzIUOGDBo0qKCgoEWLFp06dYrFYtu2bcvNzT3llFOys7OTyeT06dPz8vK2bdvWqlWrIUOG\nDBs2bIceLr300vRZBlu3bm3cuHGzZs1qOUigbo+Xr/nYg4atrv98bK/T3mCP2sPfpnb2+3dK\nLBaLx+O+4O1LysvLKysrvacQQigpKYnH45mZmfU9EKhnlZWV5eXlmZmZ8Xi8vsdC3dghZvyK\nCntmHDvTrFmznj173nTTTffee+/8+fNfeumlIUOGpHeF/z3xs7r0Kc01f4nZ1ebNmzfv1atX\n+uGUKVMSicSIESNCCK+99lpubu7AgQP79+8/Z86cJ598slWrVoMGDarefOzYsentadOmFRYW\ntmjRojavABBCqNvjZVsd9gV7XF3/+RCMshfbw9+mvrzSqLpGjRrF43Ff8PYllZWVlZWVzZs3\nt5SeiEsmk6lg1EcclJaWlpeXN2nSpOafS9mLfO0Zow3i5kshhNNOOy2E8O6776ZL2rdvH0LY\nuHHjDjU3bdoUQmjatOl+++1XQ4ffpPmKFSveeOONiy++OHVB0hkzZnTu3Pm666478cQTx48f\n36FDhxkzZuzK5AAAAACAhqWhBKOp36a2bfv/zvTq3r17CGH16tU71Fy5cmUI4ZBDDqn5p93d\nbl5VVTVp0qQuXbqce+65IYTy8vLPPvusV69eqfqxWKx3796ffvppeXn5rs0QAAAAAGgwGkow\numDBghBChw4d0iU9e/Zs06bNxo0bly9fXr3mnDlzQgj9+vWrucPdbv7SSy+tWbPmJz/5SeqK\nEqk8NHVjspTUdqNGDeWlAwAAAAB21Z5O9xYsWDB9+vTqZ4aWlJQ8++yzL730UgjhzDPPTJfH\nYrHzzjsvhDBp0qT0zSLnzJkzb968Fi1a7HCJz+nTp0+YMOHtt9/eveZpmzdvnjp16sCBA/v0\n6ZMqycjIyMrKWrZsWeqWTVVVVcuXL+/YsePXXr0VAAAAAGiw9nS6t2XLlieffDI3N/eggw5q\n1apVYWHhxo0bE4lELBbLycnp27dv9crnnXfeokWL3nvvvdGjR/fu3Xvr1q2rVq1q1KjRT3/6\n05YtW1avuXTp0oULF3bp0uWkk07ajeZpkydPjsViV1xxRfXCnJyciRMn3nffff369Zs3b96G\nDRtuuOGGuntJAAAAAIA9bU8Ho9nZ2ZdeeumiRYs++eSTNWvWxGKx9u3b9+rV66yzzjr88MN3\nqByPx++44468vLxZs2YtWbIkMzPzxBNPzMnJOeyww2rzXLvafPHixXPmzBkzZkzr1q2rl59+\n+unFxcV5eXkLFixo3779mDFjTj311N2bPgAAAADQEOzpYLRt27bDhg0bNmxYLevH4/GhQ4cO\nHTq05mo///nPv0nzlKOPPnrmzJlfuWvw4MGDBw+uTScAAAAAQMPnDkIAAAAAQOTUwRmjhYWF\nTz311IoVK9q1a3fhhRf26tXrm/cJAAAAAPDt2YVg9PXXX7/xxhu7du2al5eXLvz0009PPvnk\nf/3rX6mH99xzz2OPPXbZZZfV8TABAAAAAOrOLiylf+GFFxYtWnTsscdWLxw/fnwqFW3VqlU8\nHk8kEqNGjVq1alUdDxMAAAAAoO7sQjA6d+7cEMJ3v/vddMnnn38+bdq0EMIvfvGLrVu3fvrp\np9nZ2eXl5b/97W/repwAAAAAAHVmF4LRDRs2hBC6du2aLnn11VcrKio6dux40003hRDatWt3\n1113hRBmz55d1+MEAAAAAKgzuxCMbtq0KYRw0EEHpUv+/ve/hxDOPvvsRo3+Xz8nnHBCCCF9\nyVEAAAAAgAZoF4LRVPq5bdu2dElqcf0pp5ySLmnTpk0IobS0tM4GCAAAAABQ13YhGO3YsWMI\n4X/+539SDz/66KNly5aFEE4++eR0nS1btoQQ2rdvX5djBAAAAACoU7sQjKbODL3rrru2bNlS\nWVl56623hhB69OjRo0ePdJ2lS5eGEDp06FDX4wQAAAAAqDO7EIxec801sVjsnXfead++fZs2\nbZ5++ukQwtVXX129zmuvvRZCOO644+p2lAAAAAAAdWgXgtETTjjh4YcfzsjIqKioKCwsDCEM\nHz583Lhx6QqVlZXPPvtsCGHgwIF1PlAAAAAAgLrSeJdqjx079txzz/3rX/9aUVHxf9m70zip\nqnNv2Kt6YGwmmyENCDJ5xEgORFGCYkTUaEAERJQkOCLOSjgh4aDiABinE9B4xETURMRIEBXR\nCA6AIqjkoT3KcBBoJjUiAYHupoGe6vlQb/rhRWgoqWqGuq5PVWvfe9Vd8Nvdmz9779WxY8fO\nnTvvvnX9+vWXXHJJCOGcc85JZI8AAAAAAAkVXzAaQjj22GOvuuqqvW5q1arVww8/fNAtAQAA\nAAAkVxy30mdlZdWqVWvixInJ6wYAAAAAoArEccVoSUlJcXHxKaeckrxuAAAAAACqQBxXjObk\n5IQQIpFI0poBAAAAAKgKcQSjPXr0CCF89NFHSWsGAAAAAKAqxBGM/sd//EfNmjXvv//+b775\nJnkNAQAAAAAkWxzB6IknnjhlypTNmzd36dJl2rRpO3fuTF5bAAAAAADJE8fiSyeddFIIoUaN\nGitXruzfv39GRkbz5s1r16691+IlS5YkpkEAAAAAgESLIxhdunTp7m9LS0vXrl2b4HYAAAAA\nAJIvjmD0pptuSl4fAAAAAABVJo5g9LHHHkteHwAAAAAAVSaOxZcAAAAAAI4OglEAAAAAIOXE\nHYyWlZX99a9/7du3b4sWLWrVqtW2bduKTWvXrh0/fvzjjz+e0A4BAAAAABIsjmeMhhC+/vrr\niy++eP78+RUjpaWlFa8bN248ZsyYzZs3n3zyyaeddlrCegQAAAAASKg4rhgtLi7u2bPn/Pnz\n09PT+/bt++CDD+5RUKtWrQEDBoQQZsyYkcgeAQAAAAASKo5g9Kmnnlq0aFFWVtZ777330ksv\nDR8+/Ns1559/fghhwYIFCWsQAAAAACDR4ghGX3jhhRDC3Xff3bVr133VdOjQIYSwfPnyg+8M\nAAAAACBJ4ghGFy9eHELo06dPJTXZ2dkhhM2bNx9kWwAAAAAAyRNHMFpYWBj+FX3uy65du0II\nGRnxrekEAAAAAFCV4ghGGzRoEELYsGFDJTVLly4NITRp0uQg2wIAAAAASJ44gtFOnTqFEF5/\n/fVKap555pkQQpcuXQ6yLQAAAACA5IkjGB0wYEAI4b777svLy9trweTJkydNmhRCGDhwYEKa\nAwAAAABIhjiC0csvv7xDhw7ffPNNly5dHnnkkdWrV8fGCwsL586dO2jQoEGDBkWj0W7dul14\n4YXJ6RYAAAAAIAHiWCUpIyNjxowZ3bt3X7NmzdChQ4cOHRpCWLduXZ06dSpqjj/++ClTpiS+\nTQAAAACAxInjitEQQsuWLXNzc6+//voaNWrssSkzM3PIkCEfffRRTk5O4toDAAAAAEi8OK4Y\njalfv/6ECRPuv//+efPmffbZZ1u3bs3KymrTpk337t2zs7OT0SIAAAAAQGLFHYzG1KtXr1ev\nXr169UpsNwAAAAAAVSC+W+kBAAAAAI4C3/GK0d0VFBQ899xzy5cvb9iw4SWXXHLCCScc/JwA\nAAAAAMkTRzD61ltvDR8+vGXLltOnT68Y3LBhw+mnn7569erY29GjRz/55JNXXHFFgtsEAAAA\nAEicOG6lf+WVVz755JNOnTrtPjhs2LBYKlq3bt309PSSkpIhQ4asWrUqwW0CAAAAACROHMHo\n/PnzQwhnnXVWxcg///nPqVOnhhDuu+++bdu2bdiwoWPHjsXFxf/93/+d6D4BAAAAABImjmB0\n48aNIYSWLVtWjMycObO0tLRZs2a/+c1vQggNGza85557Qghz5sxJdJ8AAAAAAAkTRzC6efPm\nEEKTJk0qRt5///0Qwk9/+tO0tP9vnlNOOSWEUPHIUQAAAACAw1AcwWgs/czPz68Yid1cf8YZ\nZ1SMNGjQIISwc+fOhDUIAAAAAJBocQSjzZo1CyH8z//8T+ztunXrli5dGkI4/fTTK2q2bt0a\nQmjUqFEiewQAAAAASKg4gtHYlaH33HPP1q1by8rKbr/99hBCmzZt2rRpU1GzZMmSEEJOTk6i\n+wQAAAAASJg4gtGbb745Eol8+OGHjRo1atCgweTJk0MIN9100+41b775Zgjhhz/8YWK7BAAA\nAABIoDiC0VNOOeWxxx7LzMwsLS0tKCgIIQwcOPCWW26pKCgrK/vrX/8aQjj77LMT3igAAAAA\nQKJkxFV94403XnjhhW+//XZpaWnHjh07d+68+9b169dfcsklIYRzzjknkT0CAAAAACRUfMFo\nCOHYY4+96qqr9rqpVatWDz/88EG3BAAAAACQXHHcSg8AAAAAcHQQjAIAAAAAKSeOW+nHjBlz\n4MV33HFH/M0AAAAAAFSFOILRO++888CLBaMAAAAAwGErjmA0Ozt7r+OlpaX5+fnRaDSEULt2\n7Ro1aiSmNQAAAACA5IgjGN20adO+NhUUFLz++uv/+Z//WVZW9sorr/zwhz9MRG8AAAAAAEmR\nmMWX6tSpc9llly1cuDAtLe2CCy746quvEjItAAAAAEAyJHJV+kaNGt15550bN2584IEHEjgt\nAAAAAEBiJTIYDSF069YthPDqq68mdloAAAAAgARKcDCamZkZQ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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"\n",
"p <- reply_edits_1edit_bywiki_experience %>%\n",
" ggplot(aes(x=wiki, y= percent_users, fill = wiki)) +\n",
" facet_wrap(~experience_level) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" geom_text(aes(label = paste(round(percent_users * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of users\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Percent of Junior and Senior contributors that posted only 1 comment with the reply tool \\n across all opt-out wikis\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = cbp1) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position = 'bottom',\n",
" axis.title.x = element_blank(),\n",
" axis.text.x=element_blank()\n",
" ) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/one_comment_users_overall_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The chart above breaks down those overall percentages by editor experience for each wiki. The majority of users that made 1 comment are junior contributors with under 100 cumulative edits. On Arabic Wikipedia, almost half (48%) of users that made just 1 comment were junior contributors.\n",
"\n",
"Under 15% of senior contributors with over 500 cumulative edits made only 1 comment. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Distribution of Users by Number of Reply Tool Edits "
]
},
{
"cell_type": "code",
"execution_count": 372,
"metadata": {},
"outputs": [],
"source": [
"#Divide reply edits int0 edit count groups with bin width set to 5 edits\n",
"b <- c(0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, Inf)\n",
"names <- c('1-5 comments', '6-10 comments', '11-15 comments', '16-20 comments', '21-25 comments', '26-30 comments', '31-35 comments',\n",
" '36-40 comments', '41-45 comments', '46-50 comments', 'over 50 comments')\n",
"\n",
"reply_edits_byeditgroup <- collect_reply_tool_users %>%\n",
" mutate(num_reply_comments = cut(reply_edit_count, breaks = b, labels = names)) "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Overall by Wiki"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
" reply_edits_byeditgroup_overall <- reply_edits_byeditgroup %>%\n",
" group_by(wiki, num_reply_comments) %>%\n",
" summarise(n_users = n()) %>%\n",
" mutate(percent_reply_users = n_users/sum(n_users))"
]
},
{
"cell_type": "code",
"execution_count": 374,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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vN7/5zRdtNX36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\n994777zzxRdfnDx58r/+9a/bb7+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VOnhg8f7uHhIX6O/ZUdEBDQtWtX1auUT0IVqlRJQhWqNFMlGc3DQRWqUIUqVGmvSjKa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\nKs49pXCVw2FV8cC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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"p <- reply_edits_byeditgroup_overall %>%\n",
" ggplot(aes(x=num_reply_comments, y = percent_reply_users)) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" facet_grid(~wiki) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of comments with the reply tool\",\n",
" title = \"Distribution of reply tool users by number of comments \\n across all opt-out wikis\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_numcomments.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The distribution of reply tool users by the number of comments is similar across all three opt-out wikis.\n",
"Over 80% of reply tool users on each of the three opt-out wikis made between 1 to 5 comments. Hungarian Wikipedia had the highest percentage of users (20%) that made over 5 comments using the reply tool.\n",
"\n",
"Based on the number of 1 comment users provided earlier, about 30% of reply users in each wiki made between 2 to 5 comments.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### By Wiki and Editor Experience"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
" # by edit count\n",
"reply_edits_byeditgroup_bywiki <- reply_edits_byeditgroup %>%\n",
" group_by(wiki, edit_count_bucket, num_reply_comments) %>%\n",
" summarise(n_users = n()) %>%\n",
" mutate(percent_reply_users = n_users/sum(n_users))\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# by junior and senior contributors\n",
"reply_edits_byexperience_bywiki <- reply_edits_byeditgroup %>%\n",
" group_by(wiki, experience_level, num_reply_comments) %>%\n",
" summarise(n_users = n()) %>%\n",
" mutate(percent_reply_users = n_users/sum(n_users))"
]
},
{
"cell_type": "code",
"execution_count": 383,
"metadata": {},
"outputs": [
{
"data": {
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HF110UXZ2duMB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\nAAAAaUcxCgAAAACkHcUoAAAAAJB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Vljdq1Kh+tOVLFAAAIABJREFU/fqlpaUXLlwggwwyyJAwwz6SxJNBBhlk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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"p <- reply_edits_byeditgroup_bywiki %>%\n",
" filter(wiki == 'arwiki') %>%\n",
" ggplot(aes(x=num_reply_comments, y = percent_reply_users)) +\n",
" facet_grid(~edit_count_bucket) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of comments with the reply tool\",\n",
" title = \"Distribution of reply tool users by number of comments \\n and editor experience on Arabic Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_numcomments_arwiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 378,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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XDBgwoGZl//79H3vssWnTpk2fPr2goGDp0qW5ublJeGUA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RxABElmiiIYhEE4kmEk00BJFo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\nwcFGjNOIlH6fJScnr169uqysbNCgQXz4PkOetAt5giRpF5KEIE84nj59u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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# by senior and junior contributors\n",
"\n",
"p <- reply_edits_byexperience_bywiki %>%\n",
" filter(wiki == 'arwiki',\n",
" experience_level != 'NA') %>%\n",
" ggplot(aes(x=num_reply_comments, y = percent_reply_users)) +\n",
" facet_grid(~experience_level) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of comments with the reply tool\",\n",
" title = \"Distribution of Reply Tool Junior and Senior Contributors by number of comments \\n on Arabic Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_numcomments_arwiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 379,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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MB+LYVidPLkyenLAQAAAADQalIoRhuVlpbOmzfvD3/4w7p168rLy4uL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\nRfjf6nN3ampqQgh5eand0wkAAAAAoDWlUIx27do1hLBx48ZmxqxatSqE0KN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2rFixQggRGCfZRAAAIABJREFUExPTvHlzMsgggwwZMmxm3a9iPBlkkEGG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\nNjo5ORHrnePBgwcmfxtrFfCKY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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"p <- reply_edits_byeditgroup_bywiki %>%\n",
" filter(wiki == 'cswiki') %>%\n",
" ggplot(aes(x=num_reply_comments, y = percent_reply_users)) +\n",
" facet_grid(~edit_count_bucket) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of comments with the reply tool\",\n",
" title = \"Distribution of reply tool users by number of comments \\n and editor experience on Czech Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_numcomments_cswiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 380,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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ioqmDdlCCFeXl70O7b19fVjx449c+YM/7szdXV1V69edXV1vXHjhrD4JS1FYpo3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\nxE/S5cuX6YKLi0uvXr0kPaN//etfTAz83r9/v2jRIjpAUl9fn3t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LFtl50V8EOdg5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\nXgSjAABArhg0aNCgQYNqr/nZz34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NB45EE4kDR6KJhgNHookBiCxx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\ndJlMFhwc3K1bN+I8VJWbm+vj49OlSxdLRw1WxWY7KN0zQFvonZD+qYX0T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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# by senior and junior contributors\n",
"\n",
"p <- reply_edits_byexperience_bywiki %>%\n",
" filter(wiki == 'cswiki',\n",
" experience_level != 'NA') %>%\n",
" ggplot(aes(x=num_reply_comments, y = percent_reply_users)) +\n",
" facet_grid(~experience_level) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of comments with the reply tool\",\n",
" title = \"Distribution of Reply Tool Junior and Senior Contributors by number of comments \\n on Czech Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_numcomments_cswiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 381,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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710uSJo455pi33npr4cKFo0aNij6zhxdrmDhx4mGHHZaV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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"p <- reply_edits_byeditgroup_bywiki %>%\n",
" filter(wiki == 'huwiki') %>%\n",
" ggplot(aes(x=num_reply_comments, y = percent_reply_users)) +\n",
" facet_grid(~edit_count_bucket) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of comments with the reply tool\",\n",
" title = \"Distribution of reply tool users by number of comments \\n and editor experience on Hungarian Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_numcomments_huwiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 382,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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oo4+uqKiILefl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agkg0kWhy2bExWlPl5eVTpkw5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\naNEiMjJy8+bNhw8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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# by senior and junior contributors\n",
"\n",
"p <- reply_edits_byexperience_bywiki %>%\n",
" filter(wiki == 'huwiki',\n",
" experience_level != 'NA') %>%\n",
" ggplot(aes(x=num_reply_comments, y = percent_reply_users)) +\n",
" facet_grid(~experience_level) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of comments with the reply tool\",\n",
" title = \"Distribution of Reply Tool Junior and Senior Contributors by number of comments \\n on Hungarian Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_numcomments_huwiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A few key observations regarding the distbution of users by comments posted for each wiki:\n",
"\n",
"* Similar to overall trends, the majority editors across all experience levels make between 1 to 5 comments using the reply tool. Senior contributors are more likely to make more than 5 comments compared to Junior contributors.\n",
"* Over 90% of junior contributors on each of the three opt-out wikis made between 1 to 5 comments using the reply tool. \n",
"* Arabic Wikipedia had the highest percentage (22%) of senior contributors with 1000+ edits that made over 50 comments. This may be due to unmarked bots."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Distribution of people who posted a comment with the tool on distinct days"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* We reviewed the number and percentage of people overall that used the tool on just 1 day and that made edits within identified buckets of day. \n",
"\n",
"Notes: \n",
"* For this analysis, we changed the bin width to just 1 day instead of 5 days since a large majority of reply tool users in each wiki only used the reply tool between 1 to 5 distinct days. With this change, we can see more detail about reply tool usage at this level.\n",
"* Similar to the calculations above, we reviewed data comes from mediawiki_history. We reviewed all edits made with the `discussiontools` change tag.\n",
"* A distinct day was defined as a distinct calendar day; therefore, some of these edits may have occurred 24 hours apart and some may have occured only a few hours apart depending on what time of day the edit was made; however, it provides a useful estimation of repeat usage of the tool or \"stickiness of the tool\"."
]
},
{
"cell_type": "code",
"execution_count": 384,
"metadata": {},
"outputs": [],
"source": [
"query <- \"\n",
"-- obtain distinct day of edits by user\n",
"SELECT\n",
" wiki,\n",
" reply_user,\n",
" CASE\n",
" WHEN min(edit_count) is NULL THEN 'undefined'\n",
" WHEN min(edit_count) = 0 THEN '0 edits'\n",
" WHEN (min(edit_count) >=1 AND min(edit_count) < 5) THEN '1-4 edits'\n",
" WHEN (min(edit_count) >=5 AND min(edit_count) < 100) THEN '5-99 edits'\n",
" WHEN (min(edit_count) >=100 AND min(edit_count) < 1000) THEN '100-999 edits'\n",
" ELSE '1000+ edits'\n",
" END AS edit_count_bucket,\n",
" CASE\n",
" WHEN min(edit_count) < 100 THEN 'junior contributors (< 100 cumulative edits)' \n",
" WHEN min(edit_count) > 500 THEN 'senior contributors (> 500 cumulative edits)'\n",
" ELSE 'NA'\n",
" END AS experience_level,\n",
" COUNT(DISTINCT(day_of_activity)) AS days_of_activity\n",
"FROM (\n",
" SELECT\n",
" wiki_db AS wiki,\n",
" event_user_id AS reply_user,\n",
" event_user_revision_count AS edit_count,\n",
" to_date(event_timestamp) AS day_of_activity\n",
" FROM wmf.mediawiki_history\n",
" WHERE \n",
" ARRAY_CONTAINS(revision_tags, 'discussiontools') AND\n",
" snapshot = '2020-12' AND\n",
" event_timestamp >= '2020-09-24' AND\n",
" event_timestamp < '2020-12-08' AND\n",
" wiki_db IN ('arwiki','cswiki', 'huwiki') AND \n",
" event_entity = 'revision' AND\n",
"-- remove anonymous users\n",
" event_user_id IS NOT NULL AND\n",
"-- remove bots\n",
" SIZE(event_user_is_bot_by_historical) = 0 AND\n",
" SIZE(event_user_is_bot_by) = 0 AND\n",
" event_type = 'create'\n",
") edits\n",
"GROUP BY \n",
" reply_user, \n",
" wiki\n",
"\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"collect_reply_days_activity <- wmfdata::query_hive(query)"
]
},
{
"cell_type": "code",
"execution_count": 386,
"metadata": {},
"outputs": [],
"source": [
"# Order edit counts \n",
"collect_reply_days_activity$edit_count_bucket %<>% \n",
" factor(levels= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\")) \n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### By Wiki"
]
},
{
"cell_type": "code",
"execution_count": 387,
"metadata": {},
"outputs": [],
"source": [
"#Divide days of activity into groups with bin width set to 1 day\n",
"b <- c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, Inf)\n",
"names <- c('1 day', '2 days', '3 days', '4 days', '5 days', '6 days', '7 days',\n",
" '8 days', '9 days', '10 days', 'over 10 days')\n",
"\n",
"reply_days_bygroup <- collect_reply_days_activity %>%\n",
" mutate(days_activity_group = cut(days_of_activity, breaks = b, labels = names))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"reply_days_bygroup_overall <- reply_days_bygroup %>%\n",
" group_by(wiki, days_activity_group) %>%\n",
" summarise(n_users = n()) %>%\n",
" mutate(percent_reply_users = n_users/sum(n_users) * 100)"
]
},
{
"cell_type": "code",
"execution_count": 389,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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lNkTqT9rq3li9GtW7eWlJSEECZMmLDf35krKytDCHl5eXtNz87Ozs3N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\nrRq3cuXKuXPnlpSUNDwEcvz48ev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RjhgVQnh5ef3jH/9wd3e/+8qP\nQojs7GwhRKdOnbQB8fHxO3bs8Pb2btSokfEuASlbkv4ekkgiiSSzPFXWIvOORBJuXpJIIokk\nkkyMkYgkkkgiiSTT4FR6GR08ePDs2bPh4eF2dna6Gzdu3Hj8+PHevXuPHTtWqVQaNcDZ2blL\nly779u27+7jokpKSnTt3ZmdnOzg4/Pbbb2vXrhVCvPHGG02bNrWoJD09JJFEEknmeqqsReYd\niSTcvCSRRBJJJJkYIxFJJJFEEkkmwMSodAIDA5OTky9evHjgwIHAwEAPD4/y8vJff/31hx9+\naNCgwfjx411dXU2QUVxc7Ofn9+eff549e7by37e3t3dGRsbp06eTkpIuXryoUChGjRrVp08f\nC0y6Xw9JJJFEkhmfKmuFDCORhJuXJJJIIokkk2EkIokkkkgiyTQUdx/sCrMrLCxcsGCB9swR\nFxeX0tLS0tJSIcT48eP79+9v7O9+7dq1qKioEydOVL4xPDx86tSp2r9vtVodFxd3+PBhZ2fn\nvn37tmnTxtKSqu0hiSSSSDL9U2XtMuNIJOHmJYkkkkgiyfQYiUgiiSSSSDIBJkYlpVKp1q9f\n/9tvv92+fVsI4erqOmrUqJ49exr7++bl5U2bNi03N9ff3z8yMrJx48YnT55cu3ZtYWFhlb9v\nk5EtSbYekkgiiSQjMctIJOHmJYkkkkgiyVwYiUgiiSSSSDI2TqWXlLW1dYcOHQYNGtS9e/f+\n/fu/8sorAQEBJvi+MTExJ0+eDAwM/Oijj5o3b/7II4+0bt36iSee2L1795kzZ+5eM8ICk2Tr\nIYkkkkgyErOMRBJuXpJIIokkksyFkYgkkkgiiSRj46r0RldeXl5YWFizx1pbWzdt2rRp06Ym\n+3tKSkoSQowaNaryGuc+Pj7jx48XQtzvWmMWlSRbD0kkkURSterQSCTh5iWJJJJIIunhMRKR\nRBJJJJEkJyZGjau8vPyjjz6aM2dOQUGBuVsMUlxcLITw8vKqcvsTTzxhZWWlUChM//ctW5Js\nPSSRRBJJ+tWtkUjCzUsSSSSRRNJDYiQiiSSSSCJJWkyMGte//vWvpKSk8+fPz507t068DvDz\n8xNCaNc4r0ylUmk0msGDB7u7u3t5eZnyiGjZkmTrIYkkkkjSr26NRBJuXpJIIokkkh4SIxFJ\nJJFEEknSYmLUiNLT03///XdbW1t3d/e68jqgb9++QohVq1bdunWr8u2bN2/WaDS+vr4rVqyI\njIy05CTZekgiiSSS9KhzI5GEm5ckkkgiiaSHwUhEEkkkkUSSzLj4khEtW7bsypUrQ4cOHTt2\n7L59+zIzM//8889u3brZ2tqaO+2+AgMDk5OTL168eODAgcDAQA8Pj/Ly8l9//fWHH35o0KDB\n+PHjXV1dLTxJth6SSCKJJD3q3Egk4eYliSSSSCLpYTASkUQSSSSRJDNFnTjhvy7Ky8sbO3as\nk5PTV199ZWdnl5WVNXv27Nzc3MDAwIULFzo5OZk78L4KCwsXLFigPSLaxcWltLS0tLRUCDF+\n/Pj+/fuTJGGPhSeVl5evWbNm+PDhlVd9Nm+S4Ugiyajq6Egk4eYliSQ9DB+GTJb0QEgiyagY\niUgiiZGIJJIkxxGjxmJvb9+6deu2bdsGBgYKIZydnbt06VIn9pHa2tqGh4dbW1tfvnz59u3b\nFRUVrq6uEyZM0B4pXV+TysvLt2zZ0rJlS0OWwDDNJiovL1+2bJmbm5uHh4ckSUKIy5cvb9iw\nwdXV1c3NTYYk7Vr+CQkJjo6Obdq0kSFJCKHRaLKyssrLy+3t7SVJMhxJdTTpnuroSCTh5pVt\nGDJZkuHDkGmSxIMMQ6ZJeqBhyDRJ4kGGIZMlPRCS6mjSPTES1aEkRiIDMRIZgpGIpDqEI0ZN\n6n77SFNSUtq0aWOkVWlTU1MTExOzs7M9PT0jIiK0S+QaoqKi4sqVK0IIX1/f2m3bt2/f5s2b\nz58/7+bmNnTo0D59+pg3STuWJCUlhYeHT5061fCvbLxNpEvy8PD4+uuvGzRoYPakioqKlStX\nalcMady48fLly52dnc2bpNtKQojGjRt/88031tbW5k3SaDRbtmz5+eefb968KYR48skn33zz\nTUNeDRgvSQhx4sSJnTt35uXleXh4PPHEE0FBQYY8yqhJ+/bt27Zt240bNzw8PLp06fLUU08Z\n8rsz6pNSDXqMmmQ8ph+JGIaqVeNhyARJDzoMGS+pxsOQ8ZJqPAwZL6nGw5DxkkRNhyGjJkn4\ntC9hkvEwEglGogdJYiTSg5HIQIxEdTTJNJgYNbW7Xwds3749Kiqqe/fuDzoCVauioiImJmbL\nli26W2xtbWfNmhUSElKL3+VBk6Kjo//444/KN06aNMm8uxQOHjy4cOFC7cc1eClQ63TDm5OT\n06JFiwICAswYoxMdHZ2QkGBjY/Pyyy8/++yzhpymYVSVt5Knp+eFCxdmzJjRrVs3MyZVVFR8\n8skne/bsqXxjeHj4tGnTzJj0+eefb926tfKN7dq1mzJlyqOPPmqWJLVavWzZsh07dlS+0cfH\nZ+rUqS1btqTHNEw2EjEMGYhhyBAMQ9ViGDKEhE/7EiaZACMRI5F+jESGYCQyMImRqC4mmRKn\n0ptalfNHNBrN559/rlarn3jiiQ4dOtTiN9JoNEuXLk1MTLSysgoLCwsLCystLb1+/frRo0f7\n9ev3QDvcatGyZcu2b99uY2Pz/PPPv/LKK87OzqdOnbpy5cqAAQPM0qPl4ODw66+/PvHEE1lZ\nWRcvXszOzg4LCzPXSwE5XwQcO3YsJibG1tb2H//4R7du3cz196NTZSu1aNFix44dubm5vXv3\nNmPVl19+uW3bNjs7u0mTJs2cObNz5867d+++cOHC4MGDzbXFPvvss61bt9ra2r7wwgsvvfRS\nYGCg9n/c1q1bW7RoYZaXAitXroyLi7Ozs3vxxRcHDRrUrFmz9PT0nJycxMRET09Pf39/C+8x\nDdOMRAxDhmMYqhbDkCEYhgwh4dO+hEkmwEjESKQHI5EhGIkMxEhUR5NMiYlRM6j8OuDQoUMa\njSYyMjIyMrJ2v0tsbOymTZvs7OwWLFgwdOjQxx9/vE+fPqdOnUpLS2vRooWvr2/tfjtDbN++\n/aeffnJwcFi4cGHPnj0bN27csWPH/fv33759e/Dgwabv0bG3t09MTPT39x8xYsSePXvM+FLg\nfi8CNBpNTk5Obm6ug4OD4SdH1KKVK1emp6cPHjz4mWeeqXy7RqNRqVQmTrp7K3l5eW3fvv3S\npUtKpdLd3d2UMTrJycnac3wWLlwYGhpqZWXl7u6em5t75syZESNGmOW3duzYsW+//bZBgwaL\nFy8ODw/38PBo2bJlkyZN9u7dW15evnPnzsDAQB8fH1Mm5eXlffzxx0KIRYsWPf30097e3m3b\ntn322WevXbt28eLF/fv3u7q6tmjRwmJ7TMkEIxHDkOEYhqrFMFQthiFDSPi0L2GSyTASMRLd\nEyORIRiJDMRIVEeTTMzK3AEWysvLKyIiQvuxMWZFb926tXr1aiHEW2+91b59e+2NVlZW2m+a\nnp5eu9/OECqVatWqVUKIqVOntm7dWnd7WVlZ+/btjx49umnTpgMHDpSXl5u+TQjRqlWr06dP\nh4aGvvvuu9bW1tu3b1+2bJluoYmKigrTZHzyySdJSUn29vaVXwRs27Zt/PjxY8eOnTx58t//\n/veVK1eafiudO3dOCNGpUyfdLVevXl26dOnzzz8/bNiwSZMm7d271zQl93yppFAotJe9i42N\nNU3G3RITE4UQzzzzTOUlz3Nyctq1a7d79+5vvvlmzZo1GRkZpkxKSEgQQgwcOLDy/7iOHTsK\nIfz8/CoqKpYuXXr58mVTJp0+fbqioqJVq1Zt27bV3WhnZzdt2rRhw4YJIb766ivtGkmW2WNi\nRh2JGIYeFMOQfgxD1WIYMoSET/sSJpkSI5EWI1FljETVYiQyHCNRHU0yMSZGzWP79u3ff/+9\nMM6sqBDil19+KS4u7tOnT9euXSvf3rx5cyHE7du3a/07VuvYsWO5ubmhoaFdunTR3ZiYmJiZ\nmXn48OH58+d/++23ixcvfuedd3Jzc02f17p167S0tJKSkiovBdRqdUxMzMKFC1UqlQkyevbs\naW1tXVJScuHCBSGE9qyiZcuWZWdnKxQKa2vr0tLSjRs3vv/++yZ+KaBWq4UQum+akpIyZcqU\nXbt2lZWVCSHS09M/+uijX3/91QQlubm5Z8+evfu0ml69etnZ2e3evfvGjRsmyLhnmBCiSZMm\nulsOHDhw6NChlJSUqKio2NjYn3766a233tq1a5fJkrQLYFe5NqX2T2vYsGGBgYElJSUrVqww\n5UrT2u91z0MPRo4cOWDAAI1Gs3z58ry8PMvsMTGjjkQMQw+KYUg/hiFDwgTDUHUkfNqXMMmU\nGIkEI9FdGImqxUhkOEaiOppkYpxKbwZHjhxZsmSJWq020qyoEMLGxiYpKWnWrFlVrv6mUCjW\nr1/ftm1b7U4SU/Ly8rp161ZERITuwP7jx49/8sknarXa09Pz+eef79q165UrV9LS0lJTU02/\nMIqVlVV8fPzjjz/epEkTHx+fgIAA7Skku3btOnTo0PXr1zt16tS4cWNjZ+i+9YEDBzw8PE6c\nOLF+/Xrt8t4zZ8586aWXAgICjhw5kpGRoVarH3/8cWP36Bw6dOjq1asuLi6dOnUqKiqaOXNm\nQUFBp06d3n777WHDhikUijNnzvz5559du3Z1dXU1aomTk1NISEh4eHiVxYZsbW2vXbt29uxZ\nGxsbU24ZnYyMjJSUlMzMzODgYHt7+7i4uM8++6yioqJDhw6TJk0aMGBAYWHhpUuXDh482L17\nd8OvX/kwDh48mJmZ+cgjj+j2n7mumgAAIABJREFUbBcVFX300Uf5+fkjRowICwuLj4/Pzc1t\n27atydbWsbe337RpU15eXq9evRwcHKp8tmPHjkePHs3KylKpVKa5JIJsPaZk7JGIYehBMQzp\nxzBULYYhQ0j4tC9hkskwEglGonthJKoWI5HhGInqaJKJMTFqBm5ubidOnOjdu7eRZkWFEJ6e\nnj179nRzc6tye2lp6YYNG9q1a1f5iTIzM9PFxcVIJToKhaJz5866FwE5OTkzZ84sKyvr0aPH\nvHnz2rVr99hjj3Xr1i0uLi4rK6tz586PPPKIsZMqc3V1/eWXXx599NF27doJIXx8fPz9/Xfv\n3p2fny+EmDNnTlBQkGlKKr8USElJEULMnz+/R48etra2CoXC19f30Ucf3bNnz6VLlwYPHmxl\nZaKDvouLiw8fPnz58uVevXodPHhwx44dXbt2fe+99xo3buzk5NSpU6ezZ89euXLF0dHRBGNw\no0aN7v7bFkI0adLkP//5T0ZGxoABA0y/hE1gYGBSUlJ2dvZ//vOfdevWHTp0SK1WP/3007Nn\nz/b29nZ3d3/yySe1ryltbW1N80Lc1tZ2165dZ8+eVSgUjRo1SklJ+fjjjzMzM1u3bj18+HA3\nNzftb83e3t5kI5yDg8OZM2euXLly7dq1u6+YaWVl5evru3Xr1szMTNP8ecvWY0rGHokYhh4U\nw5B+DEPVYhgyhIRP+xImmQwjESPR/TASVYuRyECMRHU0ycTq4Y8kPzs7u8WLFxtvVlTrnk+U\n2uP8Kz9Fbt++fdKkSaZfiMTT03PIkCHPPffcW2+9ZWtrq73R1dW1WbNmQoicnBwT91hbWz/2\n2GNnzpzR3XLixAndEfU7d+405dH12rNXrKysSktLIyMjq4ys2qfsoqIiU54i8cwzzzRu3Lik\npCQ6OvratWsKhWLixImVD7Zv1aqVEOLmzZsmS7qbn59fhw4d8vPzt2/fbvrv7uTk9Omnn770\n0ktPP/30yy+/3K5du0ceeWTy5Mm6kUOhUGiXtjHZLy4sLKx///5qtXr16tWTJk368MMPr1y5\n4uvrO2PGDO0dtH9amZmZpunRGj16tK2t7d69ezds2HD3Z9u2bevs7FxUVJSVlWWZPSZjgpGI\nYeiBMAzpxzBULYYhA0n4tC9hkmkwEjES6cFIVDOMRFUwEtXdJFNiYtQ8GjRoYJbvW1JSIoTQ\nPTFt3749KipKrVYXFBSYPiYyMrLKWFJWVqZdjNlkx7FX1rp1a93rgJiYmM2bN9vY2AwfPvzu\npcdNQPtSwNHRUbcgvY52FFEoFKY5+0DLzs7ujTfesLKyOnTo0Pbt2xs1atSoUaPKd9Duy/X2\n9jZZ0j0NGDBAmG/FcTs7u+HDh7/99tvPPfdcSkpKx44dda9xtbR/YKa8BOr48eMnTZrk5eUl\nhHBzcxs6dOinn36qOwdK+5bAxsbGZD1CCD8/v7FjxwohVq1adfdvSq1Wa5f2N9muSNl6TMks\nIxHDkB4MQ3owDBmCYcgQEj7tS5hkMoxEjER6MBLVDCNRFYxEdTTJlMwzPQdz0b4O0P63170I\nMN5Spw9q7dq1BQUFzZo18/f3N/13b9Wq1caNG7Ozs3/77Tfti4D33nuvU6dOLVu2/PDDD728\nvO65GrHxhIaGRkVFVVkUSQixadMmIURQUJCdnZ0pezp16jR+/PivvvpKu4L1mTNntDtFhRD/\n+c9/jh49amtrGx4ebsqku3Xp0sXT0/Py5cvHjh0zy8I6Wjdv3tRoNNoNpRMbG3v27NmGDRs+\n88wzpozp27dv3759NRrN3X/Ahw4dEkK0aNGi1r9peXl5aWmpo6Pj/ZJyc3N/+umnb775Jjs7\ne9SoUbrXIlu2bCkqKvLw8NC+djFNkll6LBbDkB4MQ/oxDBmOYahuDUPmSrJYjER6MBLpx0hk\nOEYiCZ/2JUySBGuMWparV68mJCQolcrs7GzZXgRs3bp15cqVCoVi+vTpla9kZzJOTk6//vpr\ncnLy/v37dS8ChBA+Pj5PPfVUlctZmiypyi0JCQlr1qxRKBTvvPOObn0ik2nRokWTJk0OHjyo\n0WgOHDjg4OCQn5+/bt26n3/+WQgxbtw4Mw69WgqFQqVSHTt27Pbt208//bS5MpycnGJjY7Oy\nskpLS9u0aVNUVPTTTz+tXr1aCDFhwoQOHTqYPunuFwG///57bGysra3tlClT7l5j+2GUl5d/\n9NFHW7Zs6datW5VdxDodOnRo2LDhsWPHzpw5s2PHDpVKdePGjdjY2HXr1gkhJk2apD2JzGRJ\nJu6xZAxDejAMVYthyEAMQ3VuGDJ9kiVjJNKDkahajEQGYiSS7WlfwiR5KEx5MDzM7tixY3Pn\nzu3QoUNycrI8LwIqKipWrlyp3e83evToQYMGmavk9ddfz8jIqPwiQB4VFRXffffd5s2bhRBj\nxowZOHCguUouXLgQHR19/vx53S3W1tajR4+++yQXs7h9+/arr76qUqm+++47E69YX1lCQkJ0\ndLT2Y4Xir2faV155ZejQoeZK0snJyfn555//+9//CiFef/31Z599tna//v/7f//vt99+E0IE\nBgYuXLjw7pezOseOHYuOjq68hJZCoXj11Vdr/UnAwCST9VgyhiH9GIYMwTBkCIYhUQeHIVMm\nWTJGIv0YiQzBSGQIRiIh09O+hEnyYGLUsiQlJS1atEj7sSQvAhISEjZu3JiZmWlrazthwoRe\nvXqZMSYrK2v+/PkTJkyQ7UVAbGzsxo0bc3NzZdhKWkePHj169OjNmze9vLx69OhhllWQ7mfF\nihUeHh5m//NOSEj47rvvtOtV+fj4vPbaaya71qEeGRkZ06ZNKykpsbOzGzduXK3/LaWnp7/5\n5pvW1tbOzs65ubnVjrvl5eU7duw4fPhwfn6+j49P3759AwICzJhkgh4LxzCkH8OQ4RiGqsUw\nVBeHIdMkWThGIv0YiQzHSFQtRiJJnvYlTJIKE6OW5fTp0zNnztRoNJK8CBBCHDly5MMPPwwN\nDX3hhReaNm1q7hxRUVFR+SKVkkhOTl64cKFSqZRkK0muqKiodk+FqDGVSnX58uWGDRv6+vqa\neEkmPU6cOHHhwoXw8PAqC8bXivfff//IkSPDhw9/5plnZs+ebci4a2wSJlkyhqFqMQzVAwxD\n+jEMmT3JwjESVYuRqB5gJNKPkcjsSVJhYtTibN++PTs7+4UXXjB3yB3afTXmrpCdSqUy8cXy\ngAeVl5c3duxYJyenr776ys7OLisry+zjroRJYBiqoxiGID8Jn/MlTIJgJKqzGIkgPwmf9iVM\nkg0XX7I4zZs3b9++vbkr/keDBg3MnVAHSLjbFqjC3t6+devWbdu2DQwMFEI4Ozt36dJl3759\nmZmZf/75p551vi0qCQxDdRTDEOQn4XO+hEkQjER1FiMR5Cfh076ESbJhYhQAUGuaNGlS+WKF\nesbdlJSUxo0bm+CEGgmTAABGIuFzvoRJwP9v787Dm6rSB46f0C0tLW3pQrdQoCw6IIvDJpuD\ntjKgqIxY5ClIQUbkAeF5dJQBGToMMAwijoOCoLIqKotSWjZlLasgw1rZCrRAQ6F0gZaWljbN\n74/7TJ78spGkSW5ovp+/yr2n97y59+a86cvJPQCcxw2HfTcMya1QGAUAOJHJvLt37945c+YU\nFBT07NnT9XnXDUMCADiJG475bhgSAMB53HDYd8OQZERhFADgXAZ5V6vVLlq0qK6u7qmnnnri\niScICQDgVG445rthSAAA53HDYd8NQ5ILiy8BAFxB95xv6Z/usBSsG4YEAHASNxzz3TAkAIDz\nuOGw74YhuR4zRgEArhAUFFRXV3fy5EnhNhnXDUMCADiJG475bhgSAMB53HDYd8OQXK+R3AEA\nADzC3r17V69eLdwp47phSAAAJ3HDMd8NQwIAOI8bDvtuGJLrURgFADjd8ePHP/nkk7q6OvfJ\nuG4YEgDASdxwzHfDkAAAzuOGw74bhiQLb7kDAAA0fL/73e/atWvXuXNn98m4bhgSAMBJ3HDM\nd8OQAADO44bDvhuGJAsWXwIAuEJtba23t3P/N06tVmdkZLz55pteXl5uEhIAwE24Zsy3KROR\nhgDAo5CJ3BOLLwEAXKFRI+c+vKWiomLq1KknT5708vLq0KGDO4QEAHAfLhjzbc1EpCEA8Chk\nIvfEKQAANAQZGRk3b97s0KHDkCFD5I4FAOCJyEQAAHmRiexAYRQA8GhTq9X37t07ffp0UFDQ\n1KlT/fz85I4IAOBZyEQAAHmRiezm6Y8SAAA80goKCqZNm9a0aVOFQtGjR4+goCC5IwIAeBYy\nEQBAXmSi+qAwCgB4hIWGhkZFRZ07d04IERcXJ3c4AACPQyYCAMiLTFQffJUeAPAIUyqVM2fO\nfPzxx4UQR44cKSoqkjsiAIBnIRMBAORFJqoPVqUHADzavL29+/btm52dXVBQcObMmT59+vj6\n+sodFADAg5CJAADyIhPZjcIoAODRU1pampubW1tbKz1AR/c5ICcn5+TJk3wOAAA4G5kIACAj\ngzQkyET2Umi1WrljAADAWiUlJUuXLv3ll1+k/NW2bdu33347Pj5eCFFVVZWWlnbu3LmEhIRZ\ns2YFBgbKHSwAoAEiEwEAZGQhDQkyke2YMQoAeGTcvHlzypQpFy9eVCqVPXv2DA4OPnfu3N69\nezt06BAREaH7P9KLFy/yf6QAAGcgEwEAZGQ5DQm9eaNkIitRGAUAPBo0Gs20adMKCgoee+yx\nefPmJSYmPnjw4NixY7W1tQkJCW3bthX//3NAVFRU69at5Y4aANBwkIkAADKyJg0JMpGN+Co9\nAODRsH379sWLF6tUqvnz5wcEBPz000+LFy/WarVjx4598cUXNRqNl5eX1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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"p <- reply_days_bygroup_overall %>%\n",
" ggplot(aes(x=days_activity_group, y = percent_reply_users)) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" facet_grid(~wiki) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of distinct days using the reply tool\",\n",
" title = \"Distribution of reply tool users by days of activity \\n across all opt-out wikis\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_distinctdays.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"On the three opt-out wikis, the majority (60% to 69%) only used the reply tool on one day within the reviewed timeframe (24 September 2020 through 08 December 2020). Arabic Wikipedia had the highest percentage of 1 day users (69% of reply tool users posted a comment on just 1 distinct day).\n",
"\n",
"Hungarian Wikipedia had the highest overall percentage of return reply tool users (40% of reply tool users used the reply tool on more than 1 distinct day).\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Breakdown of users that posted a comment on only 1 day by experience level"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Find overall number of users that made only 1 edit by edit count\n",
"reply_days_activity_1day_byeditcount <- collect_reply_days_activity %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_wiki_user_count = n()) %>%\n",
" filter(days_of_activity == 1) %>%\n",
" group_by(wiki, edit_count_bucket) %>%\n",
" summarise(percent_users = n()/total_wiki_user_count) %>%\n",
" distinct()\n"
]
},
{
"cell_type": "code",
"execution_count": 509,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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IDyUzEjRtu2bduoUaO2bdu2adNm3LhxBw8e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\nrFkzh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hqFGjynaFVcCuObEyXFuju4rL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\nAAQAAAAASUVORK5CYII=",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot 1 edit completion rates\n",
"\n",
"p <- reply_days_activity_1day_byeditcount %>%\n",
" ggplot(aes(x=wiki, y= percent_users, fill = wiki)) +\n",
" facet_wrap(~edit_count_bucket) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" geom_text(aes(label = paste(round(percent_users * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of users\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Percent of users that posted a comment with the reply tool on only 1 day \\n by editor experience across all opt-out wikis\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = cbp1) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position=\"bottom\",\n",
" axis.title.x=element_blank(),\n",
" axis.text.x=element_blank(),\n",
" axis.ticks.x=element_blank())\n",
" \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/one_comment_users_byeditcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n",
"reply_days_activity_1day_byexperience <- collect_reply_days_activity %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_wiki_user_count = n()) %>%\n",
" filter(days_of_activity == 1,\n",
" experience_level != 'NA') %>%\n",
" group_by(wiki, experience_level) %>%\n",
" summarise(percent_users = n()/total_wiki_user_count) %>%\n",
" distinct()"
]
},
{
"cell_type": "code",
"execution_count": 510,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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LEj\nGAUAAAAAYuf/ANH7ZFfXPZ7MAAAAAElFTkSuQmCC",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot 1 edit completion rates\n",
"\n",
"p <- reply_days_activity_1day_byexperience %>%\n",
" ggplot(aes(x=wiki, y= percent_users, fill = wiki)) +\n",
" facet_wrap(~experience_level) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" geom_text(aes(label = paste(round(percent_users * 100), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of users\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Percent of Junior and Senior Contributors that posted a comment with the reply tool on only 1 day \\n across all opt-out wikis\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = cbp1) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position = 'bottom',\n",
" axis.title.x = element_blank(),\n",
" axis.text.x=element_blank()\n",
" ) \n",
" \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/one_comment_users_byexperience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The majority of 1 days reply tool users are Junior Contributors (under 100 cumulative edits) for each of the three opt-out wikis. "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
" # find distinct days by edit count and wiki\n",
"reply_days_byeditcount_bywiki <- reply_days_bygroup %>%\n",
" group_by(wiki, edit_count_bucket, days_activity_group) %>%\n",
" summarise(n_users = n()) %>%\n",
" mutate(percent_reply_users = n_users/sum(n_users))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
" # find distinct days by experience and wiki\n",
"reply_days_byexperience_bywiki <- reply_days_bygroup %>%\n",
" filter(experience_level != 'NA') %>%\n",
" group_by(wiki, experience_level, days_activity_group) %>%\n",
" summarise(n_users = n()) %>%\n",
" mutate(percent_reply_users = n_users/sum(n_users))"
]
},
{
"cell_type": "code",
"execution_count": 399,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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4Tw1ltvpawYAAAAAIAoJBCM/uIXv2jZsuXkyZNLS0tTVxAAAAAAQKol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\nTU1Np06dzjzzzKuuumqLW7tfccUV7du3/z//5//88pe/bNas2XHHHTd58uT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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"p <-reply_days_byeditcount_bywiki %>%\n",
" filter(wiki == 'arwiki') %>%\n",
" ggplot(aes(x=days_activity_group, y = percent_reply_users)) +\n",
" facet_grid(~edit_count_bucket) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of distinct days using the reply tool\",\n",
" title = \"Distribution of reply tool users by days of activity \\n and editor experience on Arabic Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_distinctdays_arwiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 400,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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CwsnDdv3oUXXti6detYwfz5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\nwQQAAAAA8K0WRzA6e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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"p <-reply_days_byexperience_bywiki %>%\n",
" filter(wiki == 'arwiki') %>%\n",
" ggplot(aes(x=days_activity_group, y = percent_reply_users)) +\n",
" facet_grid(~experience_level) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of distinct days using the reply tool\",\n",
" title = \"Distribution of reply tool Junior and Senior Contributors by days of activity \\n on Arabic Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_distinctdays_arwiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 401,
"metadata": {},
"outputs": [
{
"data": {
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6Nbtmy5ePHi3bt3P//8c+t+NkRERBARc0FrTdXV1SqVaujQ\nob6+vsHBwSyOoHOcyO847hMRh81nPsEWIHYwxNlyIr/jrJKoy3baj/i+xXm/gyEOm89m4+pi\nOwWIHQxxtpyIOLvefGwRxMDoo0eP/vzzT4lE4uvra/XPhoEDBxLRtm3bnj17pjn94MGDKpUq\nLCxs/fr1Y8aMsd9Efsdxn4g4bD4zCbkAsYMhzpYT+R1nlUQtNtV+xPctzvsdDHHYfDYbVyub\nKkDsYIiz5UTE2fXmY4sgrjG6du3avLy8YcOGTZ48+fz58zKZ7MqVK926dTPteitmioqKunnz\nZk5OTmpqalRUlL+/f01Nzf79+3/++WdHR8cpU6Z4e3vbdSK/47hPRByLcdwncr+AuoRcgNjB\nEGfLifyOs0qiFptqP+L7Fuf9DoY4FuO4T+R3XK1sqgCxgyHOlhMRx2KcVRJZIbK17/azrqSk\nZPLkye7u7ps2bZJKpXK5fMGCBUVFRVFRUUuXLnV3d+d+lsrLy5csWcKcXezp6VlVVVVVVUVE\nU6ZMeeutt3iQyO84VhJramp+/fXXkSNHSqVSDuKMwu847hO5X0BNKEDsYDYYZ3gBYvPZdZxV\nEtVssP2I71uc9zsYDv/sOpHfcVpssACxgyEOBSiQOKskmo//Z4y6uLg0a9asRYsWUVFRROTh\n4dGpUyfr/t1MIpH06tVLLBY/ePCgrKxMoVB4e3tPnTqVOevYBhNramoOHz7cpEkTA68EYX7c\n2rVrfXx8/P39OYhjPHjw4I8//vD29vbx8bF0InMp9MTERDc3t+bNm1s6johUKpVcLq+pqXFx\nceEgzih293aw8TgtKEDz43hfgFy2HxlZgKzsLShAa8VZJVHNBtuP7G2Lc9x+xPcCxOGfdRP5\nHafFBgvQ7nYw3h/+kTEFyPHhHyuJtlyA/I6zSqL5+H/GaK3q+rtZRkZG8+bNTbgQ7O3bt5OS\nkvLz8wMCAmJjY5krzr6SQqHIy8sjorCwMKNCz58/f/Dgwbt37/r4+AwbNmzAgAEG/qIJiUyL\nXbx4sVevXh9//LFR82lOnL+//+bNmx0dHS0ax/xWfHw8c80LPz+///znPx4eHpZLVC8gEfn5\n+f3www9isdhycSqV6vDhw7t27Xr69CkRde3adebMmYZ8PJgWx7h+/fqpU6dKSkr8/f07d+7c\nunVri8adP3/+5MmTxcWWCZPpAAAgAElEQVTF/v7+nTp16t69u4Gr1LREjuMsgd0CNK39iPMC\nNC2O3wXIcfuRGQVoWhz3BWha+5kcx30d2XsB2sjhH5mxxfl6+Ed8L0Ac/rGeiMM/Ywnz8M+0\nRH4f/pEZBcjx4Z9pibw//CNTG0mwh3+GEOjAKNX22ZCcnLxu3boePXoYVX8KheLHH388fPiw\neopEIvnss8/at29vidlWKBQbNmw4ceKE5sTp06dbbvT90qVLS5cuZX424bPBKOrSdHd3X7Zs\nWcOGDS0UpGnDhg2JiYlOTk7jx49/4403DDm332SaCxgQEHDv3r25c+d269bNQnEKhWL16tVn\nz57VnNirV6/Zs2dbLnHjxo3Hjx/XnBgdHT1r1qygoCDW45RK5dq1a1NSUjQnhoaGfvzxx02a\nNLH3OItipQA5bj9CAbKNy/Yjvhcgv9vPKokWgsM/A3HZfsT3AuR3+xHfC5A37Uc4/DMYvw//\nCAXIahyX7UcoQIvh/1fp66L1nQKVSrVx40alUtm5c+dWrVoZ+CIqlWrVqlVJSUkODg4xMTEx\nMTFVVVWFhYXp6emDBg0y6q89Blq7dm1ycrKTk9OIESMmTJjg4eGRmZmZl5c3ePBg1rMYrq6u\n+/fv79y5s1wuz8nJyc/Pj4mJscRng1U+Fa5evfrjjz9KJJKvvvqqW7dulthkaloL2Lhx45SU\nlKKiov79+1so8fvvvz958qRUKp0+ffq8efM6dOhw5syZe/fuDR061EJL+u233x4/flwikYwe\nPXrcuHFRUVHM/nn8+PHGjRuz/vEQHx9/9OhRqVT6P//zP++8805kZOSjR48KCgqSkpICAgIa\nNGhg13EWZX4Bct9+hAJkFZftRwIoQH63n1USLQSHfwbirP2I7wXI+/Yjvhcgb9qPcPhnMB4f\n/hEKkFUctx+hAC1GuAOj9H8/G9LS0lQq1ZgxY8aMGWP4KyQkJBw4cEAqlS5ZsmTYsGFt2rQZ\nMGBAZmbmw4cPGzduHBYWxu4MJycn//77766urkuXLu3Tp4+fn1/btm0vXLhQVlY2dOhQdrPU\nXFxckpKSGjRoMGrUqLNnz1ros6GuTwWVSlVQUFBUVOTq6mr4KfeGi4+Pf/To0dChQ/v27as5\nXaVSVVdXs5iou4DBwcHJycn3799//fXXfX192QpSu3nzJvNdjKVLl3bs2NHBwcHX17eoqCgr\nK2vUqFGWWJlXr1796aefHB0dly9f3qtXL39//yZNmgQGBp47d66mpubUqVNRUVGhoaFsxZWU\nlHzzzTdEtGzZsp49e4aEhLRo0eKNN9548uRJTk7OhQsXvL29GzdubKdxHDCzADluP0IBsv2e\n5az9SAAFyO/2s0qiReHwzxDctB/xvQB5337E9wLkWfsRDv8Mw+PDP0IBsofj9iMUoCU5WHsG\nrCw4ODg2Npb52djD4mfPnu3YsYOIPvroo5YtWzITHRwcmBd89OgRu7NaXV29bds2Ivr444+b\nNWumnv7y5cuWLVump6cfOHAgNTW1pqaG3Vwiatq06a1btzp27Dh//nyxWJycnLx27Vr1RRgU\nCoX5EatXr7548aKLi4vmp8LJkyenTJkyefLkDz/8cOzYsfHx8awv3Z07d4ioXbt26imPHz9e\ntWrViBEjhg8fPn369HPnzpmfUuvHnkgkYm7KlpCQYH6ErqSkJCLq27ev5vWtCwoKoqOjz5w5\n88MPP/z666+5ubksJiYmJhLRkCFDNPfPtm3bElFERIRCoVi1atWDBw/Yirt165ZCoWjatGmL\nFi3UE6VS6ezZs4cPH05EmzZtYq5lY49x3DC5ADluP0IBWqAAuWk/EkYB8rv9rJJoaTj8MwQH\n7Ue8LkAhtB/xvQD5136Ewz/D8PXwj1CAdnv4RyhASxL6wGhycvL27dvJ+MNiItq3b9+LFy8G\nDBjQpUsXzen169cnorKyMvZmk4jo6tWrRUVFHTt27NSpk3piUlKSTCb7+++/Fy9e/NNPPy1f\nvvzTTz8tKipiN7pZs2YPHz6srKzU+mxQKpU//vjj0qVLq6urzYzo06ePWCyurKy8d+8eETHf\n7Fi7dm1+fr5IJBKLxVVVVXv37v3yyy/Z/WxQKpVEpH7NjIyMWbNmnT59+uXLl0T06NGjr7/+\nev/+/WamFBUVZWdn635Fol+/flKp9MyZM8XFxWZG1BpKRIGBgeopqampaWlpGRkZ69atS0hI\n+P333z/66KPTp0+zlchcWVnrPoPMBh0+fHhUVFRlZeX69evZuq4x8zq1/uX23XffHTx4sEql\n+s9//lNSUmKPcdwwuQA5bj9CAVqgALlpPxJGAfK7/aySaGk4/DMEB+1HvC5AIbQf8b0A+dd+\nhMM/w/D18I9QgHZ7+EcoQEsS9FfpL1++vHLlSqVSacJhMRE5OTldvHjxs88+07rHmUgk2rNn\nT4sWLZg/F7AlODj42bNnsbGx6tPOr127tnr1aqVSGRAQMGLEiC5duuTl5T18+PD27dvsXrbD\nwcHh2LFjbdq0CQwMDA0NbdiwIfOdgtOnT6elpRUWFrZr187Pz8+cCPXLpqam+vv7X79+fc+e\nPcwFoefNmzdu3LiGDRtevnw5NzdXqVS2adOGrUVLS0t7/Pixp6dnu3btKioq5s2b9/z583bt\n2n3yySfDhw8XiURZWVlXrlzp0qWLt7e3ySnu7u7t27fv1auX1oVjJBLJkydPsrOznZycWFwo\nRm5ubkZGhkwme+2111xcXI4ePfrtt98qFIpWrVpNnz598ODB5eXl9+/fv3TpUo8ePQy/E6se\nly5dkslk9erVU/8FsqKi4uuvvy4tLR01alRMTMyxY8eKiopatGjByvVWXFxcDhw4UFJS0q9f\nP1dXV61H27Ztm56eLpfLq6urWbkYPMdxHDCnADluP0IBWqAAuWk/EkYB8rv9rJJoUTj8MxAH\n7Ue8LkAhtB/xvQB51n6Ewz+D8fXwj1CAdnv4RyhASxL0wKiPj8/169f79+9vwmExEQUEBPTp\n08fHx0drelVV1R9//BEdHa35VpfJZJ6enubMrUgk6tChg/pToaCgYN68eS9fvuzdu/cXX3wR\nHR3dqFGjbt26HT16VC6Xd+jQoV69eubEafL29t63b19QUFB0dDQRhYaGNmjQ4MyZM6WlpUS0\naNGi1q1bm5+i+dmQkZFBRIsXL+7du7dEIhGJRGFhYUFBQWfPnr1///7QoUMdHNg52fnFixd/\n//33gwcP+vXrd+nSpZSUlC5duixcuNDPz8/d3b1du3bZ2dl5eXlubm5mFreXl5furkJEgYGB\nR44cyc3NHTx4MLvXPYmKirp48WJ+fv6RI0d2796dlpamVCp79uy5YMGCkJAQX1/frl27Mp/r\nEomEleMYiURy+vTp7OxskUjk5eWVkZHxzTffyGSyZs2ajRw50sfHh1mZLi4urFSnq6trVlZW\nXl7ekydPdO9s6ODgEBYWdvz4cZlMxsoOw3EcB8wpQI7bj1CAFihAztqPBFCA/G4/qyRaFA7/\nDMRN+xGvC5D37Ud8L0CetR/h8M9gfD38IxSg3R7+EQrQkux77s0klUqXL19u2mExo9a3OnMW\nuuabPDk5efr06exeSiMgIOAf//jHm2+++dFHH0kkEmait7d3ZGQkERUUFLCYJRaLGzVqlJWV\npZ5y/fp19Tnhp06dYuv8cOarCg4ODlVVVWPGjNHqYqZQKioqWDzxvm/fvn5+fpWVlRs2bHjy\n5IlIJJo2bZrm6eJNmzYloqdPn7KVqCUiIqJVq1alpaXJycnsvrK7u/uaNWvGjRvXs2fP8ePH\nR0dH16tX78MPP1R3lkgkYq6Hwtb6jImJeeutt5RK5Y4dO6ZPn75ixYq8vLywsLC5c+cyT2A2\nqEwmYyWOiCZNmiSRSM6dO/fHH3/oPtqiRQsPD4+Kigq5XG6PcZZmZgFasf0IBcgGq7cf8agA\ned9+Vkm0HBz+GYiz9iPhFSBv2o8EUIB8aj/C4Z/B+Hr4RyhAez78IxSgxQh6YJSIHB0dWX/N\nyspKIlK//ZKTk9etW6dUKp8/f85u0JgxY7Ra7OXLl8zlhNk6W1utWbNm6g+GH3/88eDBg05O\nTiNHjtS9FrWZmM8GNzc39UXB1Zj+EolErHzxhyGVSmfMmOHg4JCWlpacnOzl5eXl5aX5BOZv\ndyEhIWwl6ho8eDBZ5hLUUql05MiRn3zyyZtvvpmRkdG2bVv1MQSD2aYs3kFyypQp06dPDw4O\nJiIfH59hw4atWbNG/TUT5oDJycmJrbiIiIjJkycT0bZt23RXoFKpZK6MztbfrziO4wDrBchZ\n+xEK0Gy20H7EowLkd/tZJdGicPhnIM7aj4RXgLxpP+J7AfKs/QiHfwbj5eEfoQDt+fCPUIAW\nw/5xITCfDcwbQP3BYNp1rIy1c+fO58+fR0ZGNmjQgN1Xbtq06d69e/Pz8w8dOsR8KixcuLBd\nu3ZNmjRZsWJFcHBwrRflNU3Hjh3XrVundfEaIjpw4AARtW7dWiqVspVFRO3atZsyZcqmTZuY\nyydnZWUxfyUjoiNHjqSnp0skkl69erGYqKVTp04BAQEPHjy4evUq61daYTx9+lSlUjELqJaQ\nkJCdne3s7Ny3b18WswYOHDhw4ECVSqW7S6SlpRFR48aNjXrBmpqaqqoqNze3uuKKiop+//33\nH374IT8/Py4uTv3Zc/jw4YqKCn9/f+azyjbjeMaK7UcoQONZvf2IXwXIevuR3kayRB2hAM2B\nwz/zCaoA+dR+hMM/tB8O/8yD//+yjq+Hf4QCtAxBX2PUQh4/fpyYmPj666/n5+dz+cFw/Pjx\n+Ph4kUg0Z84czXuxscLd3X3//v03b968cOGC+lOBiEJDQ7t37651a0JW4rSmJCYm/vrrryKR\n6NNPP1VfaIYtjRs3DgwMvHTpkkqlSk1NdXV1LS0t3b17965du4jogw8+sFBfM0QiUXV19dWr\nV8vKynr27GmJCHd394SEBLlcXlVV1bx584qKit9//33Hjh1ENHXq1FatWrGeqPvB8OeffyYk\nJEgkklmzZulevLkuNTU1X3/99eHDh7t166b15z61Vq1aOTs7X716NSsrKyUlpbq6uri4OCEh\nYffu3UQ0ffp05vs1NhjHP9ZqP0IBmsq67Ud8LEC22o8MaCR26wgFaCYc/rGVqDWFrwXIv/Yj\nHP4JFQ7/2IrTmoL//5qDx4d/hAK0ABGLX4EBxtWrVz///PNWrVrdvHmTmw8GhUIRHx/P/EFp\n0qRJ77zzjiVS/vnPf+bm5mp+KnBDoVBs3br14MGDRPT+++8PGTLEQkH37t3bsGHD3bt31VPE\nYvGkSZN0v9TAurKysokTJ1ZXV2/dupXFq4ZrSkxM3LBhA/OzSPT/3/gTJkwYNmyYJeI0FRQU\n7Nq166+//iKif/7zn2+88Ybhv/vf//730KFDRBQVFbV06VLdIwa1q1evbtiwQfPqQiKRaOLE\niUa9HTiO4x/u249QgGywYvsRrwvQnPYjgxuJrTpCAZoJh3+s430B8rj9CId/QoLDP9bh/7+s\n4PfhH6EAWYWBUfZdvHhx2bJlzM8cfDAkJibu3btXJpNJJJKpU6f269fPQkFyuXzx4sVTp07l\n8lMhISFh7969RUVFll46tfT09PT09KdPnwYHB/fu3Zv1q9XUZf369f7+/hbdWxITE7du3cpc\n7ic0NPS9995j6wZ5euTm5s6ePbuyslIqlX7wwQdGbcFHjx7NnDlTLBZ7eHgUFRW9sqxrampS\nUlL+/vvv0tLS0NDQgQMHNmzY0GbjeInj9iMUIKus1X7E0wI0p/3IyEYyv45QgObD4R+7BFKA\nvGw/wuGfwODwj134/y+L+H34RyhA9mBglH23bt2aN2+eSqXi5oPh8uXLK1as6Nix4+jRo8PD\nwy2apVAoNG84yIGbN28uXbr09ddf52DprKuiosKoc+xNU11d/eDBA2dn57CwMHavC6bH9evX\n792716tXL60Le7/Sl19+efny5ZEjR/bt23fBggWGlLU5OI7jJY7bj1CAfMHXAjS5/QgFaIdw\n+McugRQgX9uPcPgnJDj8Y5dA2o/4W4A4/LNHGBi1iOTk5Pz8/NGjR3MTx/xFgpss7lVXV7N7\nKzewCyUlJZMnT3Z3d9+0aZNUKpXL5RYta47jeIzj9iMUIPARCtBO4fCPXShAAUL72Skc/rEL\n7SdMKEArws2XLKJ+/fotW7bkLM7R0ZGzLO5xf5IC2AIXF5dmzZq1aNEiKiqKiDw8PDp16nT+\n/HmZTHblyhU9F4e2izge47j9CAUIfIQCtFM4/GMXClCA0H52Cod/7EL7CRMK0IowMAoANiow\nMFDzDnd6yjojI8PPz8/ML0dwHAcAoAcKEACECe0HAIKFArQWDIwCgN2otayTk5OXL18ul8tj\nYmLYLWuO4wAA9EABAoAwof0AQLBQgNzAwCgA2BOtslapVBs3blQqlZ07d27VqpW9xwEA6IEC\nBABhQvsBgGChADmAmy8BgP1RXxya+aelb4LJcRwAgB4oQAAQJrQfAAgWCtCicMYoANgfDw8P\npVJ55coV4qSmOY4DANADBQgAwoT2AwDBQgFalIO1ZwAAwGjJycnbt28nrmqa4zgAAD1QgAAg\nTGg/ABAsFKBFYWAUAOzM5cuX161bp1QqualpjuMAAPRAAQKAMKH9AECwUICW5mjtGQAAME6L\nFi2aNm3atm1bbmqa4zgAAD1QgAAgTGg/ABAsFKCl4eZLAGB/ampqHB3N+ruOTCY7ePDgBx98\nIBaLOYgDAGCLmY1kVPuZHwcAwBYc/gGAYKEALQo3XwIA++PgYNZlQMrLy+fPn3/lyhWxWNyy\nZUtLxwEAsMicRjK2/cyMAwBgEQ7/AECwUIAWJaylBQAgooMHD+bn57ds2XLo0KHWnhcAAO6g\n/QBAsFCAACBYKED9MDAKAAIik8meP39+7do1Dw+P+fPnOzs7W3uOAAC4gPYDAMFCAQKAYKEA\nDSGgqwYAgMDJ5fIFCxbUq1dPJBJ16tTJw8PD2nMEAMAFtB8ACBYKEAAECwVoIAyMAoBQ+Pj4\nBAUFZWZmElFYWJi1ZwcAgCNoPwAQLBQgAAgWCtBA+Co9AAiFVCpdsmRJ8+bNiSg1NbWwsNDa\ncwQAwAW0HwAIFgoQAAQLBWgg3JUeAATE0dGxe/fuN27ckMvl169f79atm0QisfZMAQBYHNoP\nAAQLBQgAgoUCNAQGRgGA50pKSnJycmpqapiLqqg/G7Kzs69cuYLPBgDgK7QfAAgWChAAhEmr\n/QgFaACRSqWy9jwAAFhEcXHx5s2bL1y4wBRdkyZNPvzww8jISCKqrKxcvHhxZmZmVFTU0qVL\n3d3drT2zAACsQfsBgGChAAFAmPS0H6EA9cIZowDAT/n5+fPmzbt9+7ZUKo2JifHy8srMzExO\nTm7ZsqW/v7/672a3b9/G380AgE/QfgAgWChAABAm/e1HGueNogB1YWAUAHhIoVAsWLBALpc3\na9Zs5cqV/fr1e/nyZVpaWk1NTVRUVJMmTej/fjYEBQU1atTI2nMNAGAutB8ACBYKEACEyZD2\nIxRg3fBVegDgoaNHj3733Xfh4eGrVq1ydXU9duzYd999p1Kp3n///SFDhigUCrFYzDyzsrLy\nzJkz/fr1s+4MAwCwAu0HAIKFAgQAYTK8/QgFWBsHa88AAAD7UlNTieiDDz7Q/WAgouPHj//0\n00/MM6VSKT4VAIA30H4AIFgoQAAQJsPbj1CAtcHAKADw0NOnTx0cHFq3bp2YmKj1waBUKvfv\n33/gwIFHjx5ZezYBAFiG9gMAwUIBAoAwof3MhIFRAOADrauCBAQEKJXKbdu2ffvtt5ofDEQU\nHx8vk8lat24dHh5ujTkFAGCZZgGi/QBAUFCAACBMaD8WYWAUAOxebm7uF198oTmlR48eRLR3\n716tD4bjx4/v37/f0dExLi6O+/kEAGCdVgGi/QBAOFCAACBMaD92YWAUAOzeli1brl69euXK\nFfWUrl27vvbaa0Tk7e3dqFEjlUpVUFDw/fffr1+/noimTJmCe/ABAD9oFSDaDwCEAwUIAMKE\n9mMX7koPAHbv7NmzK1eubN++vebfzSoqKpYsWZKZmUlEDg4OSqWSiMRi8XvvvTd48GCrzSsA\nAKt0CxDtBwACgQIEAGFC+7FL/OWXX1p7HgAAzBIWFnbixIk7d+706NHD09OTmejk5NS7d2+p\nVFpQUPD8+XM3N7eOHTt+8sknHTt2tO7cAgCwSLcA0X4AIBAoQAAQJrQfu3DGKADwwf79+7ds\n2TJo0KCpU6fqPqpSqUQiEfdzBQDAAT0FiPYDAH5DAQKAMKH9WIRrjAIAHwwYMMDFxeXEiRPl\n5eW6j+KDAQB4TE8Bov0AgN9QgAAgTGg/FmFgFADsTG5u7v79+ysqKjQnurq69uvXr7Ky8tix\nY9aaMQAAS0MBAoBgoQABQJjQfpaGa4wCgD159uzZnDlzzp8/f+jQoadPn4aGhrq7uzMPhYaG\nHjp0SCaTxcbG4q9kAMA/KEAAECwUIAAIE9q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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"p <-reply_days_byeditcount_bywiki %>%\n",
" filter(wiki == 'cswiki') %>%\n",
" ggplot(aes(x=days_activity_group, y = percent_reply_users)) +\n",
" facet_grid(~edit_count_bucket) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of distinct days using the reply tool\",\n",
" title = \"Distribution of reply tool users by days of activity \\n and editor experience on Czech Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_distinctdays_cswiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 402,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"p <-reply_days_byexperience_bywiki %>%\n",
" filter(wiki == 'cswiki') %>%\n",
" ggplot(aes(x=days_activity_group, y = percent_reply_users)) +\n",
" facet_grid(~experience_level) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of distinct days using the reply tool\",\n",
" title = \"Distribution of reply tool Junior and Senior Contributors by days of activity \\n on Czech Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_distinctdays_cswiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 403,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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SGWIJZMEpFNQiQy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\nuVAikcyZM2f06NFEtGHDBuZeN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"text/plain": [
"plot without title"
]
},
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}
},
"output_type": "display_data"
}
],
"source": [
"p <-reply_days_byeditcount_bywiki %>%\n",
" filter(wiki == 'huwiki') %>%\n",
" ggplot(aes(x=days_activity_group, y = percent_reply_users)) +\n",
" facet_grid(~edit_count_bucket) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of distinct days using the reply tool\",\n",
" title = \"Distribution of reply tool users by days of activity \\n and editor experience on Hungarian Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_distinctdays_huwiki_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 403,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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CSo27ZtGzVq1M0339y5c+dn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\nM8+ccsopbdq0Oe+881avXl0vvQM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pZvknNHAxNoYjvAAAIABJREFUECgUHig00EigUHig0ECj6gMFP2kKIZTf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\ny9ixYx0cHJS2NzY2/vTTT35+foq/rsRicefOnQ0bYFsxDDN06FB5WlxSU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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"p <-reply_days_byexperience_bywiki %>%\n",
" filter(wiki == 'huwiki') %>%\n",
" ggplot(aes(x=days_activity_group, y = percent_reply_users)) +\n",
" facet_grid(~experience_level) +\n",
" geom_bar(stat = 'identity', fill = 'darkblue') +\n",
" geom_text(aes(label = paste(round(percent_reply_users * 100), '%')), vjust = -0.5) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of reply tool users\",\n",
" x = \"Number of distinct days using the reply tool\",\n",
" title = \"Distribution of reply tool Junior and Senior Contributors by days of activity \\n on Hungarian Wikipedia\") +\n",
" theme_bw() +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.text.x = element_text(angle=45, hjust=1)) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_users_by_distinctdays_huwiki_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A few key observations regarding the distbution of users by distinct days of activity for each wiki:\n",
"\n",
"* Arabic Wikipedia had the highest percentage of junior contributors (83%) that made a post with the reply tool on 1 day (compared to 70% on Hungarian Wikipedia). This makes sense as Arabic Wikipedia also had the most junior contributors that made 1 comment.\n",
"* Arabic Wikipedia had the highest percentage of senior contributors with over 1000 edits that made edits on over 10 distinct days\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 3. Are people posting disruptive comments?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To determine if reply tools users are posting disruptive comments, we reviewed the percent of comments reverted within 48 hours and well as the percent of users blocked after posting a reply."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Percent of comments posted using the Reply Tool that are reverted within 48 hours"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For this analysis, we reviwed data recorded in [mediawiki_history](https://wikitech.wikimedia.org/wiki/Analytics/Data_Lake/Edits/MediaWiki_history) to identify comments posted by the reply tool (identified by the revision tag: `discussiontools`) that are reverted within 48 hours [1]. \n",
"\n",
"We included both anonymous and registed users as this analysis does not look at reverts on a per user basis and does not require the ability to identifiy unqiue users. Reverts were reviewed on a per comment basis instead. \n",
"\n",
"[1] 48 hours is a common cutoff, as [research](https://meta.wikimedia.org/wiki/Research:Revert) suggests that, at least for the English Wikipedia, nearly all reverts take place within 48 hours\n"
]
},
{
"cell_type": "code",
"execution_count": 404,
"metadata": {},
"outputs": [],
"source": [
"# collect comments posted using the Reply Tool reverted within 48 hours.\n",
"query <- \"\n",
"SELECT\n",
" wiki_db AS wiki,\n",
" CASE\n",
" WHEN event_user_revision_count is NULL THEN 'undefined'\n",
" WHEN event_user_revision_count = 0 THEN '0 edits'\n",
" WHEN (event_user_revision_count >=1 AND event_user_revision_count < 5) THEN '1-4 edits'\n",
" WHEN (event_user_revision_count >=5 AND event_user_revision_count < 100) THEN '5-99 edits'\n",
" WHEN (event_user_revision_count >=100 AND event_user_revision_count < 1000) THEN '100-999 edits'\n",
" ELSE '1000+ edits'\n",
" END AS edit_count_bucket,\n",
" CASE\n",
" WHEN event_user_revision_count < 100 THEN 'junior contributors (< 100 cumulative edits)' \n",
" WHEN event_user_revision_count > 500 THEN 'senior contributors (> 500 cumulative edits)'\n",
" ELSE 'NA'\n",
" END AS experience_level,\n",
" SUM(CAST(\n",
" revision_is_identity_reverted AND \n",
" revision_seconds_to_identity_revert <= 172800 -- 48 hours\n",
" AS int)) AS num_reverts,\n",
" COUNT(*) as num_comments\n",
"FROM wmf.mediawiki_history mh \n",
"WHERE \n",
" snapshot = '2020-12'\n",
" AND ARRAY_CONTAINS(revision_tags, 'discussiontools')\n",
" AND event_entity = 'revision'\n",
" AND event_type = 'create'\n",
" AND event_timestamp >= '2020-09-24' \n",
" AND event_timestamp <= '2020-12-08'\n",
" AND wiki_db IN ('arwiki','cswiki', 'huwiki')\n",
" AND SIZE(event_user_is_bot_by_historical) = 0 \n",
" AND SIZE(event_user_is_bot_by) = 0\n",
"GROUP BY \n",
" wiki_db ,\n",
" CASE\n",
" WHEN event_user_revision_count is NULL THEN 'undefined'\n",
" WHEN event_user_revision_count = 0 THEN '0 edits'\n",
" WHEN (event_user_revision_count >=1 AND event_user_revision_count < 5) THEN '1-4 edits'\n",
" WHEN (event_user_revision_count >=5 AND event_user_revision_count < 100) THEN '5-99 edits'\n",
" WHEN (event_user_revision_count >=100 AND event_user_revision_count < 1000) THEN '100-999 edits'\n",
" ELSE '1000+ edits'\n",
" END,\n",
"CASE\n",
" WHEN event_user_revision_count < 100 THEN 'junior contributors (< 100 cumulative edits)' \n",
" WHEN event_user_revision_count > 500 THEN 'senior contributors (> 500 cumulative edits)'\n",
" ELSE 'NA'\n",
" END\n",
"\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"collect_reply_reverts <- wmfdata::query_hive(query)"
]
},
{
"cell_type": "code",
"execution_count": 406,
"metadata": {},
"outputs": [],
"source": [
"# Order edit counts \n",
"collect_reply_reverts$edit_count_bucket %<>% \n",
" factor(levels= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\")) "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### By Wiki"
]
},
{
"cell_type": "code",
"execution_count": 486,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"A tibble: 3 × 4\n",
"\n",
"\t| wiki | total_reverts | total_comments | pct_reply_reverts |
|---|
\n",
"\t| <chr> | <int> | <int> | <dbl> |
|---|
\n",
"\n",
"\n",
"\t| arwiki | 255 | 3672 | 6.9444444 |
\n",
"\t| cswiki | 21 | 2792 | 0.7521490 |
\n",
"\t| huwiki | 20 | 2405 | 0.8316008 |
\n",
"\n",
"
\n"
],
"text/latex": [
"A tibble: 3 × 4\n",
"\\begin{tabular}{llll}\n",
" wiki & total\\_reverts & total\\_comments & pct\\_reply\\_reverts\\\\\n",
" & & & \\\\\n",
"\\hline\n",
"\t arwiki & 255 & 3672 & 6.9444444\\\\\n",
"\t cswiki & 21 & 2792 & 0.7521490\\\\\n",
"\t huwiki & 20 & 2405 & 0.8316008\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A tibble: 3 × 4\n",
"\n",
"| wiki <chr> | total_reverts <int> | total_comments <int> | pct_reply_reverts <dbl> |\n",
"|---|---|---|---|\n",
"| arwiki | 255 | 3672 | 6.9444444 |\n",
"| cswiki | 21 | 2792 | 0.7521490 |\n",
"| huwiki | 20 | 2405 | 0.8316008 |\n",
"\n"
],
"text/plain": [
" wiki total_reverts total_comments pct_reply_reverts\n",
"1 arwiki 255 3672 6.9444444 \n",
"2 cswiki 21 2792 0.7521490 \n",
"3 huwiki 20 2405 0.8316008 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pct_reverts_bywiki <- collect_reply_reverts %>%\n",
" group_by(wiki) %>%\n",
" summarise(total_reverts = sum(num_reverts),\n",
" total_comments = sum(num_comments),\n",
" pct_reply_reverts = total_reverts/total_comments * 100, .groups = 'drop')\n",
"\n",
"pct_reverts_bywiki"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"On Czech and Hungarian Wikipedia, under 1 percent of reply tool comments posted by users during the reviewed time period (24 September 2020 through 08 December 2020) were reverted under 48 hours.\n",
"\n",
"Arabic Wikipedia had a significantly higher revert rate in comparison (6.9%). However, this revert rate is similar to the desktop revert rate on content namespaces on all Wikipedia projects, which was 6.7% during the same time period."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### By Wiki and Experience level"
]
},
{
"cell_type": "code",
"execution_count": 487,
"metadata": {},
"outputs": [],
"source": [
"pct_reply_reverts_byeditcount <- collect_reply_reverts %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_comments = sum(num_comments)) %>%\n",
" group_by(wiki, edit_count_bucket) %>%\n",
" summarise(total_reply_reverts = sum(num_reverts),\n",
" pct_reply_reverts = total_reply_reverts/total_comments, .groups = 'drop')\n"
]
},
{
"cell_type": "code",
"execution_count": 511,
"metadata": {},
"outputs": [
{
"data": {
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WpqOm3atOvXr+fn55eXl9+/f3/jxo1u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\n2bOnVCpVS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fodeuihmZmZM2fOnDhx4qxZsz7++ON27dr9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\nC2i+/bsqWUSlAAAAAElFTkSuQmCC",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot revert rates by edit count and by wiki\n",
"\n",
"p <- pct_reply_reverts_byeditcount %>%\n",
" ggplot(aes(x=wiki, y= pct_reply_reverts, fill = wiki)) +\n",
" facet_wrap(~edit_count_bucket) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" geom_text(aes(label = paste(round(pct_reply_reverts * 100, 2), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" labs (y = \"Percent of users\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Percent of comments posted using the reply tool that are reverted within 48 hours \\n by editor experience across all opt-out wikis\") +\n",
" scale_fill_manual(values = cbp1) +\n",
" theme_bw() +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position = 'bottom',\n",
" axis.title.x = element_blank(),\n",
" axis.text.x=element_blank()\n",
" ) \n",
" \n",
"p\n",
"ggsave(\"Figures/reply_comment_reverts_byeditcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 491,
"metadata": {},
"outputs": [],
"source": [
"pct_reply_reverts_byexperience <- collect_reply_reverts %>%\n",
" filter(experience_level != 'NA') %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_comments = sum(num_comments)) %>%\n",
" group_by(wiki, experience_level) %>%\n",
" summarise(total_reply_reverts = sum(num_reverts),\n",
" pct_reply_reverts = total_reply_reverts/total_comments, .groups = 'drop')\n"
]
},
{
"cell_type": "code",
"execution_count": 512,
"metadata": {},
"outputs": [
{
"data": {
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K9iJn6lKpj4fd3GjRtnzpz55ptvfvbZZyGEpk2b9uvX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AyBFGAQAAAIDI\nEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAA\ngMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEA\nAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFG\nAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDI\nEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAA\ngMgRRgEAAACAyBFGAQAAAIDIEUbZa4wePTo/Pz8Wi2VkZBQXF0+fPn2nT1m+fHnv3r2zs7Nj\nsVhmZma3bt3mz5//xWXr1q078cQTc3NzEwcvKCi45JJLGjnsmjVrjjrqqMzMzIyMjAMOOGDe\nvHkN977yyiuxWOzaa69N9gUCAAAA0GSEUfYOZ5999vjx4+vq6s4444wBAwasXr162LBhzz33\nXCNPWbFiRffu3d95550DDjhg2LBhvXr1Wr58+XHHHffWW281XPbBBx8cccQRM2fOzMvL69On\nT9++fVu1avXmm282cuSTTz558eLFY8aMeeKJJzZt2nTSSSfV1dUldtXV1Y0YMaJjx47333//\n7r9qAAAAANIkq7kHgJ177733pkyZkpOT89lnn+2///4hhKlTp44cOfKiiy4aOnTolz3r+9//\nfnV19cknn/zSSy8ltjzyyCNXXHHFyJEjV6xYUb/sjDPOqKysvP3222+77bZdnGfJkiXHHnvs\n9ddfH0JYtGjR2LFj582b179//xDCBRdcsGnTpgULFnzlFwsAAABAE3DGKHuBO++8M4QwfPjw\nRBUNIYwYMaJdu3YbN27c7vTPhhYtWhRCePDBB+u3XH755bm5uStXrly1alViyx//+Me1a9f2\n6NHjtttu27Rp07Jly+rP/WxEPB7Pzc1NPC4oKAghbN26NYTwzjvvPPHEEz/4wQ969+791V4p\nAAAAAE1DGGUvkKifZ555ZsONRx11VAhh6tSpX/asmpqaEELbtm0bbszOzm74rMceeyxxqOLi\n4tatW3/961/Pyso67rjjysvLG5mnc+fOs2fPfuutt1avXj1u3Ljs7Ozjjz8+hHDqqacWFRX9\n9re//SovEgAAAIAmJIyyF9iwYUMIYbvTMA8++OAQwvLly7/sWR06dAgh/PKXv6zfsnTp0i1b\ntoQQ/vnPfya2JJ7+1FNPbdy48ZxzzrnooouKiormzp3bvXv3RuaZMWNGUVHRMccc07Fjx9LS\n0t/97nc5OTnXXHPN559//vTTT2dk+LUCAAAA2NMpOOwFqqurQwhFRUUNN+bn54d/X8O+Q7fe\nemsI4e677/7xj388c+bMBx544JhjjknsSuTREEJFRUUIIRaLrVix4o9//OOvf/3rtWvX5uXl\nffLJJ0888cSXHblHjx5r164tKSlZtmxZRUXFueeeu2LFivHjxw8ePHjQoEG33357fn5+ZmZm\n+/bt6z/eFAAAAIA9ijDKXiBx/Xt9zUwoKysLIeTl5X3Zsy666KIbb7wxFov96le/OvHEE6+5\n5poWLVr06dMnhFD/WaU5OTkhhCOPPLK4uDixJSsra9iwYSGEp556qvGpOnTocOihhyYef/e7\n383NzZ02bdof//jHO+64o2/fvokL6gcPHpw43RUAAACAPYowyl4g0THffvvthhs//vjjEELX\nrl0beeKYMWPKy8unTJly//33v/rqq+vXr1+7dm0IYcCAAYkF7du3D/++6L5e4iL9XQ+a9913\n34cffvib3/wmJydnzJgx2dnZM2fOHDVq1NSpU2tqan7+85/v4nEAAAAAaDJZzT0A7NzRRx/9\n4YcfPv3008OHD6/f+M4774Qv3JHpi3JyckaMGJF4vGrVqk8//TQzMzNxTmgI4fjjj1+4cOFn\nn33W8CnLli0LIdSfQ9q4NWvW3Hzzzf379z/77LNDCGvXri0sLEzsSuTXxNEAAAAA2KM4Y5S9\nwC233BJCmDZt2qZNmxJbpk2btnbt2latWh177LGJLXV1dY8//vjkyZMbPrG0tLT+cUVFRf/+\n/ePx+Lnnnpu4gj6EcNNNN2VkZCxdunTp0qWJLZs2bZo+fXoI4fLLL9+V2U455ZSMjIwZM2Yk\nvmzTpk39Jf/z5s0LIXzta1/7Kq8ZAAAAgHQSRtkL9OjRY/jw4ZWVlQcccMCwYcNOOOGEESNG\nxGKxRx99tH5NaWnpD3/4w1GjRjV8YqtWrTp37nzcccf16dOnsLDwk08+OeywwyZNmlS/oG3b\ntldccUU8Hj/yyCNPOOGEU045pbi4uLKy8lvf+tbJJ5+808EmTpz49ttv/+IXv2jVqlViy1VX\nXVVVVXXqqadOnz59xIgRGRkZ1157bYr+MQAAAACQMi6lZ+/wzDPP/OQnP/nNb37z3HPPxWKx\n9u3bP/zwww2vrN+h7t27f/jhh59++mksFissLBw1atQvf/nL7dbcfvvtHTt2/MUvfvHGG2/E\n4/GWLVtefPHFjz/++E5HKi8v/9GPfvSNb3zjyiuvrN942WWXLV68+NFHH/3LX/5SWFg4efLk\n7T7AFAAAAIA9gTCahHg8XltbW1tb29yDRNS4cePGjRvXcEvDn0VBQUFNTc12G//xj39sd5Ad\n/viuvPLKG2+8cafLttOiRYuysrIvLt5uTv/CsHepq6sL//7jrrlngT1CPB4PIdTV1fmliBo/\ncfgK/OLsRRLv+vwHDuol3vXV1tYmHrBv2OkfccJoEurq6srLyxMtjH1JXV2dHyskJN4EVFVV\nJf6mAUi8l9q2bVssFmvuWUilurq6zMzMRvaWlZU1sgDYIW+q9yKJMFpZWVldXd3cs8AeIfGu\nr7y8vLkHIZV2+kecMJqEzMzMgoKCoqKi5h6EVFq3bl1mZqYfKyRUV1dv3ry5RYsWLVu2bO5Z\nYI+wdevWbdu25eXlZWdnN/cspFJGRmMftZ+RkVFUVCSMQrK8qd6LVFRUlJWV7bfffrm5uc09\nC+wRtmzZUllZWVBQ0PibBPYuOw2jftgAAAAAQOQIowAAAABA5AijAAAAAEDkCKMAAAAAQOS4\n+dJe4NFHH23uEWC3XHrppc09AgAAAMD/jzNGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAA\nAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYB\nAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgR\nRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACA\nyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAA\nAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYB\nAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgRRgEAAACAyBFGAQAAAIDIEUYBAAAAgMgR\nRgEAAACAyBFGAQAAANhrjB49Oj8/PxaLZWRkFBcXT58+vfH1FRUVsR1566236tcsW7ZswIAB\nBQUFmZmZsVgsOzv7oIMOmjRpUuNHXrNmzVFHHZWZmZmRkXHAAQfMmzev4d5XXnklFotde+21\nX/mVkm5ZzT0AAAAAAOySs88+e8qUKfvtt98ZZ5yxcePGWbNmDRs2bNq0aUOHDm38ibm5uccd\nd1zDLZ06dap/vGTJkg8//LBDhw4dOnRo2bLlqlWrVq5ced555y1duvTee+/9smOefPLJixcv\nHjNmzEEHHXTJJZecdNJJpaWlGRkZIYS6uroRI0Z07Njx/vvv371XTBoJowAAAADsBd57770p\nU6bk5OR89tln+++/fwhh6tSpI0eOvOiii3YaRtu3b//yyy9/2d5hw4adeuqp+++/fyJrhhBm\nzJgxZMiQBx98sJEwumTJkmOPPfb6668PISxatGjs2LHz5s3r379/COGCCy7YtGnTggULvsLL\npMm4lB4AAACAvcCdd94ZQhg+fHiiioYQRowY0a5du40bNza8Lv7LfPrpp/Pnzy8tLd2V7zVo\n0KAQQlVVVSNr4vF4bm5u4nFBQUEIYevWrSGEd95554knnvjBD37Qu3fvXfleNBdhFAAAAIC9\nQKJ+nnnmmQ03HnXUUSGEqVOnNv7cTz75pHPnzv369SsqKmrfvv0OP5l0w4YNs2fPfuWVVx54\n4IGuXbuGEHr06NHIMTt37jx79uy33npr9erV48aNy87OPv7440MIp556alFR0W9/+9vkXh5N\nzqX0AAAAAOwFNmzYEELY7jTMgw8+OISwfPnyL3tWRkZGbm7uMcccc+ihh27ZsmXOnDmrVq0a\nNmzYlClTzjrrrIYrH3nkkVtuuSXxOBaLHXnkkTNnzmxknhkzZhx//PHHHHNMCKFFixa/+93v\ncnJyrrnmms8///zll1+uvyqfPZafEMDeKtlbMTZUXl6+3377xWKxoqKi7XatXLmyf//+2dnZ\nsVgsMzOzW7du8+fPb/xobsUIAAA0gerq6hDCdv8Xk5+fH/59DfsO5eTkbNu27fXXX3/88ccn\nT5782WefnXPOOfF4/LLLLttu5dChQ2+44Yaf/OQnJ5xwQnZ2dmVl5bZt2xqZp0ePHmvXri0p\nKVm2bFlFRcW55567YsWK8ePHDx4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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot revert rates by experience and by wiki\n",
"\n",
"p <- pct_reply_reverts_byexperience %>%\n",
" ggplot(aes(x=wiki, y= pct_reply_reverts, fill = wiki)) +\n",
" facet_grid(~experience_level) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" geom_text(aes(label = paste(round(pct_reply_reverts * 100, 2), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" labs (y = \"Percent of users\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Percent of comments posted by Junior and Senior Contributors using the reply tool \\n that are reverted within 48 hours across all opt-out wikis\") +\n",
" scale_fill_manual(values = cbp1) +\n",
" theme_bw() +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position = 'bottom',\n",
" axis.title.x = element_blank(),\n",
" axis.text.x=element_blank()\n",
" ) \n",
" \n",
"p\n",
"ggsave(\"Figures/reply_comment_reverts_byexperience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We further investigated the revert rate by breaking down the revert rate by editor experience level for each of the three opt-out wikis.\n",
"\n",
"As shown in the chart above, 5.69% of reverts were made by contributors with over 1000 edits on Arabic Wikipedia. This indicates that the reverts are not caused by an inexperienced contributor unable to correctly use the process but potentially by an unmarked bot. \n",
"\n",
"We reviewed the revert rates on full page wikitext talk page edits to compare if these are signficantly different than reply tool wikitext reverts rates."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Full Talk Page WikiText Edit Revert Rates vs. Reply Tool Wikitext Revert Rates"
]
},
{
"cell_type": "code",
"execution_count": 422,
"metadata": {},
"outputs": [],
"source": [
"# collect full page desktop wikitext edits reverted within 48 hours.\n",
"query <- \"\n",
"SELECT\n",
" wiki_db AS wiki,\n",
" CASE\n",
" WHEN event_user_revision_count is NULL THEN 'undefined'\n",
" WHEN event_user_revision_count = 0 THEN '0 edits'\n",
" WHEN (event_user_revision_count >=1 AND event_user_revision_count < 5) THEN '1-4 edits'\n",
" WHEN (event_user_revision_count >=5 AND event_user_revision_count < 100) THEN '5-99 edits'\n",
" WHEN (event_user_revision_count >=100 AND event_user_revision_count < 1000) THEN '100-999 edits'\n",
" ELSE '1000+ edits'\n",
" END AS edit_count_bucket,\n",
" CASE\n",
" WHEN event_user_revision_count < 100 THEN 'junior contributors (< 100 cumulative edits)' \n",
" WHEN event_user_revision_count > 500 THEN 'senior contributors (> 500 cumulative edits)'\n",
" ELSE 'NA'\n",
" END AS experience_level,\n",
" SUM(CAST(\n",
" revision_is_identity_reverted AND \n",
" revision_seconds_to_identity_revert <= 172800 -- 48 hours\n",
" AS int)) AS num_reverts,\n",
" COUNT(*) as num_comments\n",
"FROM wmf.mediawiki_history mh \n",
"WHERE \n",
" snapshot = '2020-12'\n",
"-- look only at desktop wikitext edits \n",
" AND NOT array_contains(revision_tags, 'visualeditor') \n",
" AND NOT array_contains(revision_tags, 'iOS')\n",
" AND NOT array_contains(revision_tags, 'Android')\n",
" AND NOT array_contains(revision_tags, 'Mobile Web')\n",
"-- review all talk page namespaces\n",
" AND page_namespace_historical % 2 == 1 \n",
" AND event_entity = 'revision'\n",
" AND event_type = 'create'\n",
" AND event_timestamp >= '2020-09-24' \n",
" AND event_timestamp <= '2020-12-08' \n",
" AND wiki_db IN ('arwiki','cswiki', 'huwiki')\n",
" AND SIZE(event_user_is_bot_by_historical) = 0 \n",
" AND SIZE(event_user_is_bot_by) = 0\n",
"GROUP BY \n",
" wiki_db ,\n",
" CASE\n",
" WHEN event_user_revision_count is NULL THEN 'undefined'\n",
" WHEN event_user_revision_count = 0 THEN '0 edits'\n",
" WHEN (event_user_revision_count >=1 AND event_user_revision_count < 5) THEN '1-4 edits'\n",
" WHEN (event_user_revision_count >=5 AND event_user_revision_count < 100) THEN '5-99 edits'\n",
" WHEN (event_user_revision_count >=100 AND event_user_revision_count < 1000) THEN '100-999 edits'\n",
" ELSE '1000+ edits'\n",
" END,\n",
" CASE\n",
" WHEN event_user_revision_count < 100 THEN 'junior contributors (< 100 cumulative edits)' \n",
" WHEN event_user_revision_count > 500 THEN 'senior contributors (> 500 cumulative edits)'\n",
" ELSE 'NA'\n",
" END\n",
"\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"collect_wikitext_talk_reverts <- wmfdata::query_hive(query)"
]
},
{
"cell_type": "code",
"execution_count": 424,
"metadata": {},
"outputs": [],
"source": [
"# Order edit counts \n",
"collect_wikitext_talk_reverts$edit_count_bucket %<>% \n",
" factor(levels= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\")) "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pct_wikitext_reverts_byeditcount <- collect_wikitext_talk_reverts %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_comments = sum(num_comments)) %>%\n",
" group_by(wiki, edit_count_bucket) %>%\n",
" summarise(total_wikitext_reverts = sum(num_reverts),\n",
" pct_fullpage_wikitext_reverts = total_wikitext_reverts/total_comments * 100)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pct_wikitext_reverts_byexperience <- collect_wikitext_talk_reverts %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_comments = sum(num_comments)) %>%\n",
" group_by(wiki, experience_level) %>%\n",
" summarise(total_wikitext_reverts = sum(num_reverts),\n",
" pct_fullpage_wikitext_reverts = total_wikitext_reverts/total_comments * 100)\n"
]
},
{
"cell_type": "code",
"execution_count": 427,
"metadata": {},
"outputs": [],
"source": [
"# collect comments posted using the Reply Tool reverted within 48 hours for wikitext only.\n",
"query <- \"\n",
"SELECT\n",
" wiki_db AS wiki,\n",
" CASE\n",
" WHEN event_user_revision_count is NULL THEN 'undefined'\n",
" WHEN event_user_revision_count = 0 THEN '0 edits'\n",
" WHEN (event_user_revision_count >=1 AND event_user_revision_count < 5) THEN '1-4 edits'\n",
" WHEN (event_user_revision_count >=5 AND event_user_revision_count < 100) THEN '5-99 edits'\n",
" WHEN (event_user_revision_count >=100 AND event_user_revision_count < 1000) THEN '100-999 edits'\n",
" ELSE '1000+ edits'\n",
" END AS edit_count_bucket,\n",
" CASE\n",
" WHEN event_user_revision_count < 100 THEN 'junior contributors (< 100 cumulative edits)' \n",
" WHEN event_user_revision_count > 500 THEN 'senior contributors (> 500 cumulative edits)'\n",
" ELSE 'NA'\n",
" END AS experience_level,\n",
" SUM(CAST(\n",
" revision_is_identity_reverted AND \n",
" revision_seconds_to_identity_revert <= 172800 -- 48 hours\n",
" AS int)) AS num_reverts,\n",
" COUNT(*) as num_comments\n",
"FROM wmf.mediawiki_history mh \n",
"WHERE \n",
" snapshot = '2020-12'\n",
" AND ARRAY_CONTAINS(revision_tags, 'discussiontools')\n",
"-- isolate to only wikitext edits\n",
" AND NOT ARRAY_CONTAINS(revision_tags, 'visualeditor')\n",
" AND event_entity = 'revision'\n",
" AND event_type = 'create'\n",
" AND event_timestamp >= '2020-09-24' \n",
" AND event_timestamp <= '2020-12-08' \n",
" AND wiki_db IN ('arwiki','cswiki', 'huwiki')\n",
" AND SIZE(event_user_is_bot_by_historical) = 0 \n",
" AND SIZE(event_user_is_bot_by) = 0\n",
"GROUP BY \n",
" wiki_db ,\n",
" CASE\n",
" WHEN event_user_revision_count is NULL THEN 'undefined'\n",
" WHEN event_user_revision_count = 0 THEN '0 edits'\n",
" WHEN (event_user_revision_count >=1 AND event_user_revision_count < 5) THEN '1-4 edits'\n",
" WHEN (event_user_revision_count >=5 AND event_user_revision_count < 100) THEN '5-99 edits'\n",
" WHEN (event_user_revision_count >=100 AND event_user_revision_count < 1000) THEN '100-999 edits'\n",
" ELSE '1000+ edits'\n",
" END,\n",
" CASE\n",
" WHEN event_user_revision_count < 100 THEN 'junior contributors (< 100 cumulative edits)' \n",
" WHEN event_user_revision_count > 500 THEN 'senior contributors (> 500 cumulative edits)'\n",
" ELSE 'NA'\n",
" END\n",
"\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"collect_wikitext_comment_reverts <- wmfdata::query_hive(query)"
]
},
{
"cell_type": "code",
"execution_count": 429,
"metadata": {},
"outputs": [],
"source": [
"# Order edit counts \n",
"collect_wikitext_comment_reverts $edit_count_bucket %<>% \n",
" factor(levels= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\")) "
]
},
{
"cell_type": "code",
"execution_count": 430,
"metadata": {},
"outputs": [],
"source": [
"experience_level_names <- c(\n",
" `junior contributors (< 100 cumulative edits)` = \"junior contributors \\n (< 100 cumulative edits)\",\n",
" `senior contributors (> 500 cumulative edits)` = \"senior contributors \\n (> 500 cumulative edits)\"\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pct_reply_wikitext_reverts_byeditcount <- collect_wikitext_comment_reverts %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_comments = sum(num_comments)) %>%\n",
" group_by(wiki, edit_count_bucket) %>%\n",
" summarise(total_reply_wikitext_reverts = sum(num_reverts),\n",
" pct_reply_wikitext_reverts = total_reply_wikitext_reverts/total_comments * 100)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pct_reply_wikitext_reverts_byexperience <- collect_wikitext_comment_reverts %>%\n",
" filter(experience_level != 'NA') %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_comments = sum(num_comments)) %>%\n",
" group_by(wiki, experience_level) %>%\n",
" summarise(total_reply_wikitext_reverts = sum(num_reverts),\n",
" pct_reply_wikitext_reverts = total_reply_wikitext_reverts/total_comments * 100)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join revert rate tables for editcount\n",
"revert_rate_comparison_editcount <- inner_join(pct_reply_wikitext_reverts_byeditcount, pct_wikitext_reverts_byeditcount) %>%\n",
"# remove uneeded columns to simplify\n",
" select(-c(3,5)) %>%\n",
"## rename columns to clarify\n",
"rename(full_talkpage_wikitext = pct_fullpage_wikitext_reverts,\n",
" reply_wikitext = pct_reply_wikitext_reverts)"
]
},
{
"cell_type": "code",
"execution_count": 494,
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot comparison between full page and reply tool completion rates by editor experience\n",
"\n",
"p <- revert_rate_comparison_editcount %>%\n",
" distinct() %>%\n",
" gather(\"edit_type\", \"revert_rate\", 3:4) %>%\n",
" ggplot(aes(x=edit_type, y= revert_rate/100, fill = edit_type)) +\n",
" facet_grid (wiki~edit_count_bucket) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" geom_text(aes(label = paste(round(revert_rate, 1), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" labs (y = \"Percent revert rate\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Reply Tool Wikitext vs Full Talk Page Wikitext Revert Rate by Editor Experience\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = c('red4', 'darkblue'), labels = c('Full Page Wikitext', 'Reply Tool Wikitext')) +\n",
" theme(\n",
" legend.position=\"bottom\",\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.title.x = element_blank(),\n",
" axis.text.x=element_blank()\n",
" ) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/fullpage_wikitext_vs_reply_revert_editcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# join revert rate tables by experience level\n",
"revert_rate_comparison_experience <- inner_join(pct_reply_wikitext_reverts_byexperience, pct_wikitext_reverts_byexperience) %>%\n",
"# remove uneeded columns to simplify\n",
" select(-c(3,5)) %>%\n",
"## rename columns to clarify\n",
"rename(full_talkpage_wikitext = pct_fullpage_wikitext_reverts,\n",
" reply_wikitext = pct_reply_wikitext_reverts)"
]
},
{
"cell_type": "code",
"execution_count": 495,
"metadata": {},
"outputs": [
{
"data": {
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IYBQAAAAAaN6QIUOO2ecMfQC3W+kBAAAA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\nhZxbaBO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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot comparison between full page and reply tool completion rates by editor experience\n",
"\n",
"p <- revert_rate_comparison_experience %>%\n",
" gather(\"edit_type\", \"revert_rate\", 3:4) %>%\n",
" ggplot(aes(x=edit_type, y= revert_rate/100, fill = edit_type)) +\n",
" facet_grid (wiki~experience_level, labeller = labeller(experience_level =experience_level_names)) +\n",
" geom_col(position = 'dodge') +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" geom_text(aes(label = paste(round(revert_rate, 1), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" labs (y = \"Percent revert rate\",\n",
" x = \"Experience Level\",\n",
" title = \"Reply Tool Wikitext vs Full Talk Page Wikitext Revert Rate for Junior and Senior Contributors\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = c('red4', 'darkblue'), labels = c('Full Page Wikitext', 'Reply Tool Wikitext')) +\n",
" theme(\n",
" legend.position=\"bottom\",\n",
" strip.text = element_text(face=\"bold\", size=12),\n",
" strip.text.y = element_text(margin = margin(1, 1, 1, 1, \"cm\")),\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" axis.title.x = element_blank(),\n",
" axis.text.x=element_blank()\n",
" ) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/fullpage_wikitext_vs_reply_revert_experience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The reply tool had a lower revert rate compared to full talk page wikitext edits for all experience levels except for Senior Contributors on Arabic Wikipedia.\n",
"\n",
"On Arabic Wikipedia, there is higher percent of wikitext reply reverts from editors with over 1000 edits (5.7% vs 2.6%) compared to the revert rate on full talk page wikitext edits. However, for contributors with under 1000 edits the reply tool revert rate is lower than the revert rate on full talk page wikitext edits."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Number of people blocked after posting a reply using DiscussionTools"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We also reviewed the number of people blocked after posting a reply using DiscussionTools.\n",
"\n",
"Data comes from the mediawiki_user_history table. All block events identifed in the data by `caused_by_event_type = \"alterblocks\".` Note this may includes users that were blocked after posting a reply but may not necessarily have been blocked due to the reply.\n"
]
},
{
"cell_type": "code",
"execution_count": 451,
"metadata": {},
"outputs": [],
"source": [
"query <- \"\n",
"\n",
"-- find users that made at least one edit with the reply tool\n",
"WITH reply_users AS (\n",
"SELECT\n",
" event_user_id as reply_user,\n",
" wiki_db as reply_wiki,\n",
" min(mh.event_timestamp) as first_reply_time,\n",
" CASE\n",
" WHEN event_user_revision_count is NULL THEN 'undefined'\n",
" WHEN event_user_revision_count = 0 THEN '0 edits'\n",
" WHEN (event_user_revision_count >=1 AND event_user_revision_count < 5) THEN '1-4 edits'\n",
" WHEN (event_user_revision_count >=5 AND event_user_revision_count < 100) THEN '5-99 edits'\n",
" WHEN (event_user_revision_count >=100 AND event_user_revision_count < 1000) THEN '100-999 edits'\n",
" ELSE '1000+ edits'\n",
" END AS edit_count_bucket,\n",
" CASE\n",
" WHEN event_user_revision_count < 100 THEN 'junior contributors (< 100 cumulative edits)' \n",
" WHEN event_user_revision_count > 500 THEN 'senior contributors (> 500 cumulative edits)'\n",
" ELSE 'NA'\n",
" END AS experience_level\n",
"FROM wmf.mediawiki_history AS mh\n",
"WHERE \n",
" ARRAY_CONTAINS(revision_tags, 'discussiontools') AND\n",
" snapshot = '2020-12' AND\n",
" event_timestamp BETWEEN '2020-09-24' AND '2020-12-08' AND\n",
" wiki_db IN ('arwiki','cswiki', 'huwiki') AND \n",
"-- remove bots\n",
" SIZE(event_user_is_bot_by_historical) = 0 AND\n",
" SIZE(event_user_is_bot_by) = 0 AND\n",
" event_entity = 'revision' AND \n",
" event_type = 'create' AND\n",
"-- remove anonymous users\n",
" event_user_id IS NOT NULL\n",
"GROUP BY\n",
" event_user_id,\n",
" wiki_db,\n",
" CASE\n",
" WHEN event_user_revision_count is NULL THEN 'undefined'\n",
" WHEN event_user_revision_count = 0 THEN '0 edits'\n",
" WHEN (event_user_revision_count >=1 AND event_user_revision_count < 5) THEN '1-4 edits'\n",
" WHEN (event_user_revision_count >=5 AND event_user_revision_count < 100) THEN '5-99 edits'\n",
" WHEN (event_user_revision_count >=100 AND event_user_revision_count < 1000) THEN '100-999 edits'\n",
" ELSE '1000+ edits'\n",
" END ,\n",
" CASE\n",
" WHEN event_user_revision_count < 100 THEN 'junior contributors (< 100 cumulative edits)' \n",
" WHEN event_user_revision_count > 500 THEN 'senior contributors (> 500 cumulative edits)'\n",
" ELSE 'NA'\n",
" END \n",
"),\n",
"--find users that are blocked sitewide\n",
"blocked_users AS (\n",
"SELECT \n",
" h1.user_id AS blocked_user,\n",
" h1.wiki_db AS blocked_wiki,\n",
" min(h1.start_timestamp) AS block_time \n",
"FROM(\n",
" SELECT *\n",
" FROM wmf.mediawiki_user_history\n",
"WHERE \n",
" snapshot = '2020-12'\n",
" AND start_timestamp BETWEEN '2020-09-24' AND '2020-12-08'\n",
" AND wiki_db IN ('arwiki', 'cswiki', 'huwiki')\n",
" AND caused_by_event_type = 'alterblocks'\n",
" AND inferred_from IS NULL) as h1\n",
"LEFT JOIN (\n",
"SELECT * FROM wmf.mediawiki_user_history\n",
" WHERE snapshot = '2020-12'\n",
" AND end_timestamp BETWEEN '2020-09-24' AND '2020-12-08'\n",
" AND wiki_db IN ('arwiki', 'cswiki', 'huwiki')\n",
" AND caused_by_event_type = 'alterblocks'\n",
" AND inferred_from IS NULL) AS h2\n",
"ON (h1.wiki_db = h2.wiki_db\n",
" AND h1.user_id = h2.user_id\n",
" AND h1.start_timestamp = h2.end_timestamp)\n",
"WHERE h2.start_timestamp IS NULL\n",
"GROUP BY h1.wiki_db, h1.user_id\n",
")\n",
"\n",
"-- Main Query --\n",
"SELECT\n",
" reply_wiki AS wiki,\n",
" edit_count_bucket AS edit_count_bucket,\n",
" experience_level AS experience_level,\n",
" SUM(CAST(blocked_user IS NOT NULL and first_reply_time < block_time AS int)) AS blocked_reply_tool_user,\n",
" COUNT(*) AS all_reply_tool_users\n",
"\n",
"FROM (\n",
"SELECT\n",
" reply_users.first_reply_time,\n",
" blocked_users.block_time,\n",
" reply_users.reply_wiki,\n",
" blocked_users.blocked_user,\n",
" reply_users.edit_count_bucket,\n",
" reply_users.experience_level\n",
"FROM reply_users\n",
"LEFT JOIN blocked_users ON \n",
" reply_users.reply_user = blocked_users.blocked_user AND\n",
" reply_users.reply_wiki = blocked_users.blocked_wiki \n",
") sessions\n",
"GROUP BY\n",
" reply_wiki,\n",
" edit_count_bucket,\n",
" experience_level\n",
"\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"collect_blocked_users <- wmfdata::query_hive(query)"
]
},
{
"cell_type": "code",
"execution_count": 453,
"metadata": {},
"outputs": [],
"source": [
"# Order edit counts \n",
"collect_blocked_users$edit_count_bucket %<>% \n",
" factor(levels= c(\"0 edits\", \"1-4 edits\", \"5-99 edits\", \"100-999 edits\", \"1000+ edits\")) "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Blocked Users by Wiki"
]
},
{
"cell_type": "code",
"execution_count": 496,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"A tibble: 3 × 4\n",
"\n",
"\t| wiki | total_blocked_users | total_reply_users | pct_blocked_reply_users |
|---|
\n",
"\t| <chr> | <int> | <int> | <dbl> |
|---|
\n",
"\n",
"\n",
"\t| arwiki | 10 | 388 | 2.5773196 |
\n",
"\t| cswiki | 4 | 455 | 0.8791209 |
\n",
"\t| huwiki | 6 | 332 | 1.8072289 |
\n",
"\n",
"
\n"
],
"text/latex": [
"A tibble: 3 × 4\n",
"\\begin{tabular}{llll}\n",
" wiki & total\\_blocked\\_users & total\\_reply\\_users & pct\\_blocked\\_reply\\_users\\\\\n",
" & & & \\\\\n",
"\\hline\n",
"\t arwiki & 10 & 388 & 2.5773196\\\\\n",
"\t cswiki & 4 & 455 & 0.8791209\\\\\n",
"\t huwiki & 6 & 332 & 1.8072289\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A tibble: 3 × 4\n",
"\n",
"| wiki <chr> | total_blocked_users <int> | total_reply_users <int> | pct_blocked_reply_users <dbl> |\n",
"|---|---|---|---|\n",
"| arwiki | 10 | 388 | 2.5773196 |\n",
"| cswiki | 4 | 455 | 0.8791209 |\n",
"| huwiki | 6 | 332 | 1.8072289 |\n",
"\n"
],
"text/plain": [
" wiki total_blocked_users total_reply_users pct_blocked_reply_users\n",
"1 arwiki 10 388 2.5773196 \n",
"2 cswiki 4 455 0.8791209 \n",
"3 huwiki 6 332 1.8072289 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pct_blocks_bywiki <- collect_blocked_users %>%\n",
" group_by(wiki) %>%\n",
" summarise(total_blocked_users = sum(blocked_reply_tool_user),\n",
" total_reply_users = sum(all_reply_tool_users),\n",
" pct_blocked_reply_users = total_blocked_users/total_reply_users * 100, .groups = 'drop')\n",
"\n",
"pct_blocks_bywiki"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Only 1.70% of all reply tool users were blocked after posting a comment across all three opt-out wikis. Arabic Wikipedia had the highest percent of blocked users (2.57% [10 reply tool users were blocked]) while Czech Wikpedia had the lowest percent of blocked users (0.88% [4 total reply tool users were blocked))."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Blocked users by Wiki and Experience Level"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pct_reply_blocks_byeditcount <- collect_blocked_users %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_reply_users = sum(all_reply_tool_users)) %>%\n",
" group_by(wiki, edit_count_bucket) %>%\n",
" summarise(total_blocked_users = sum(blocked_reply_tool_user),\n",
" pct_blocked_reply_users = total_blocked_users/total_reply_users)\n"
]
},
{
"cell_type": "code",
"execution_count": 513,
"metadata": {},
"outputs": [
{
"data": {
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l3t2rVLmis/9ezEiRMFVSu/POT111/X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\nKirq9u3bA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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"# plot revert rates by experience and by wiki\n",
"\n",
"p <- pct_reply_blocks_byeditcount %>%\n",
" ggplot(aes(x=wiki, y= pct_blocked_reply_users, fill = wiki)) +\n",
" facet_wrap(~edit_count_bucket) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" geom_text(aes(label = paste(round(pct_blocked_reply_users * 100, 2), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Number of users\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Percent of users blocked after posting a comment using the Reply Tool \\n by editor experience\") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = cbp1) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position=\"bottom\",\n",
" axis.title.x = element_blank(),\n",
" axis.text.x=element_blank()\n",
" )\n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_tool_user_blocks_byeditcount.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pct_reply_blocks_byexperience <- collect_blocked_users %>%\n",
" filter(experience_level != 'NA') %>%\n",
" group_by(wiki) %>%\n",
" mutate(total_reply_users = sum(all_reply_tool_users)) %>%\n",
" group_by(wiki, experience_level) %>%\n",
" summarise(total_blocked_users = sum(blocked_reply_tool_user),\n",
" pct_blocked_reply_users = total_blocked_users/total_reply_users)"
]
},
{
"cell_type": "code",
"execution_count": 514,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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uqOS2vQKjOJ4pAsAADvHaxKDwAAIM3PP/+8aNEi0bUKeTze5s2bCSFmZmaLFi1S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\nhpQfzIJHy8rKBPcvW7Zs/fr1dJGKqqqqiIiIxYsX9+vXz8zMLDg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eBhxKP3PmzLfeeuvYY4+tO3jNNddkqmhhYWFubssOGoYAACAASURBVG4ymbzssstW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\njUY/+OCD4447rkGDI+z2rAAAAABApWSme/v27XvkkUdCCMcff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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 600,
"width": 900
}
},
"output_type": "display_data"
}
],
"source": [
"p <- pct_reply_blocks_byexperience %>%\n",
" ggplot(aes(x=wiki, y= pct_blocked_reply_users, fill = wiki)) +\n",
" facet_wrap(~experience_level) +\n",
" geom_bar(stat='identity', position = 'dodge') +\n",
" geom_text(aes(label = paste(round(pct_blocked_reply_users * 100, 2), '%')), vjust = -0.5, position = position_dodge(width = 1)) +\n",
" scale_y_continuous(labels = scales::percent) +\n",
" labs (y = \"Percent of users\",\n",
" x = \"Edit Count Bucket\",\n",
" title = \"Percent of Junior and Senior contributors blocked \\n after posting a comment using the Reply Tool \") +\n",
" theme_bw() +\n",
" scale_fill_manual(values = cbp1) +\n",
" theme(\n",
" plot.title = element_text(hjust = 0.5),\n",
" text = element_text(size=16),\n",
" legend.position = 'bottom',\n",
" axis.title.x = element_blank(),\n",
" axis.text.x=element_blank()\n",
" ) \n",
" \n",
"p\n",
"\n",
"ggsave(\"Figures/reply_tool_user_blocks_byexperience.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"On Arabic and Hungarian Wikipedias, the largest percent of blocked users were those with between 5 to 99 cumulative edits. This is likely because the majority of reply tool users that posted a comment on these two wikis were those with 5 to 99 edits. "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "R",
"language": "R",
"name": "ir"
},
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