{ "cells": [ { "cell_type": "markdown", "id": "d4a3bb95-9d6a-44a5-bfb0-47b8f2ab3b18", "metadata": {}, "source": [ "# Topic Subscription AB Test Analysis \n", "\n", "**Megan Neisler, Senior Data Scientist, Wikimedia Foundation**\n", "\n", "** Last update: 5 August 2022**\n", "\n", "[TASK](https://phabricator.wikimedia.org/T280897) | [CODEBASE](https://github.com/wikimedia-research/Topic-notifications-analysis-2022)" ] }, { "cell_type": "markdown", "id": "234beda4-4b0c-4629-ad71-0da7fe99f836", "metadata": {}, "source": [ "# Table of Contents\n", "\n", "1. [Introduction](#Introduction)\n", "2. [Methodology](#Methodology)\n", "3. [Data exploration](#Data-exploration)\n", "4. [Key Performance Indicator](#Key-Performance-Indicator)\n", "5. [Curiosities](#Curiosities)\n", "6. [Guardrails](#Guardrails)\n" ] }, { "cell_type": "markdown", "id": "d2411e96-531e-4568-9617-f086a2febb0f", "metadata": {}, "source": [ "# Introduction\n", "\n", "The Wikimedia Foundation's [Editing team](https://www.mediawiki.org/wiki/Editing_team#:~:text=The%20Editing%20team%20is%20the,tools%20like%20TemplateData%20and%20Citoid.) is working to improve how contributors communicate on Wikipedia using talk pages through a series of incremental improvements that will be released over time.\n", "\n", "As part of this effort, the Editing team is working to to improve the notifications editors receive for the wikitext talk page conversations they are interested in. This work is intended to increase the likelihood Junior and Senior Contributors receive timely and relevant responses to the comment they post and conversations they start on wikitext talk pages, regardless of the tool used to publish these comments and conversations. \n", "\n", "The team ran an AB test of the notifications feature from 2 June 2022 through 18 July 2022 to assess the efficacy of this new feature and determine if topic subscriptions should be offered to all logged in volunteers at all Wikimedia sites by default. The test included all logged-in users that edited at one the 20 participating Wikipedias during the duration of the AB test (see full list of [participating Wikipedias in task description](https://phabricator.wikimedia.org/T304027) and conditions outlined in the methodology section below). During this test, 50% of users included in the test had the Manual and Automatic topic subsctiptions automatically enabled, and 50% did not.\n", "\n", "You can find more information about features of this tool and project updates on the [project page](https://www.mediawiki.org/w/index.php?title=Talk_pages_project/Notifications&useskin=vector-2022)." ] }, { "cell_type": "markdown", "id": "f52988f0-c2d1-43d5-b16f-15c291cfc2e1", "metadata": {}, "source": [ "# Methodology\n", "\n", "The AB test was run on a per Wikipedia basis and logged-in contributors included in the test were randomly assigned to either the control (topic subscription features disabled by default) or treatment (topic subscriptions enabled by default) based on the user Id. All of the participating wikis have access the same set of other tools: new topic and reply tool and editing interfaces.\n", "\n", "Users at these Wikipedias were still able to turn the tool on or off the topic subscription preferences in Special:Preferences; however, they remained in the same group they were buketed in for the duration of the test. For this analysis, we also did not exclude users that may have previously used or enabled the Topic Subscription feature, instead, we used available instrumentation to identify these users in the analyis when needed.\n", "\n", "Upon conclusion of the test on 15 July 2022, we recorded a total of 54,138 comments posted on a talk page by 9,997 distinct logged-in contributors across all experience levels. A total of 4,781 (48%) of these contributors were identified as Junior Contributors. \n", "\n", "We used data logged in the following sources to track user talk page behavior and preference changes during the AB test:\n", "\n", "* [EditAttemptStep](https://schema.wikimedia.org/#!//secondary/jsonschema/analytics/legacy/editattemptstep) and [talk_page_edit](https://schema.wikimedia.org/#!/secondary/jsonschema/analytics/mediawiki/talk_page_edit): Talk page edit attempts and comments by distinct users in the AB test\n", "* [Mediawiki user_properties](https://www.mediawiki.org/wiki/Manual:User_properties_table/en?useskin=vector-2022) and [discussiontools_subscription](https://www.mediawiki.org/wiki/Extension:DiscussionTools/discussiontools_subscription_table?useskin=vector-2022): Topic subscription preference changes and current status\n", "* [Echo Notification](https://www.mediawiki.org/wiki/Extension:Echo/echo_notification_table?useskin=vector-2022): Notifications sent and read by users.\n", "\n", "See the following Phabricator tickets for further details regarding instrumentation and implementation of the AB test:\n", "* [Implement Topic Subscription AB Test bucketing](https://phabricator.wikimedia.org/T304030)\n", "* [AB Test start](https://phabricator.wikimedia.org/T304029)" ] }, { "cell_type": "code", "execution_count": 123, "id": "bfbff2f1-85af-412f-9ed4-2b4d1c4a6c01", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "library(IRdisplay)\n", "\n", "display_html(\n", "'\n", "
\n", " \n", "
'\n", ")" ] }, { "cell_type": "code", "execution_count": 4, "id": "67de97eb-66e3-417b-adc2-236d57495de2", "metadata": {}, "outputs": [], "source": [ "shhh <- function(expr) suppressPackageStartupMessages(suppressWarnings(suppressMessages(expr)))\n", "shhh({\n", " library(tidyverse)\n", " library(lubridate)\n", " set.seed(5)\n", " # Tables:\n", " library(gt)\n", " library(gtsummary)\n", "})" ] }, { "cell_type": "code", "execution_count": 5, "id": "8826f2a8-9242-4745-9052-d4d7e9bcc11d", "metadata": {}, "outputs": [], "source": [ "options(repr.plot.width = 20, repr.plot.height = 20)" ] }, { "cell_type": "code", "execution_count": 6, "id": "f608bed8-a457-43da-8783-595191ef2f10", "metadata": {}, "outputs": [], "source": [ "# Collect all edit attempts that were talk page comments\n", "query <- \"SELECT\n", " date_format(eas.dt, 'yyyy-MM-dd') as attempt_dt,\n", " date_format(tpe.dt, 'yyyy-MM-dd') as save_dt,\n", " event.editing_session_id as edit_attempt_id,\n", " wiki AS wiki,\n", " event.bucket AS experiment_group,\n", " event.editor_interface as interface,\n", " event.integration as integration,\n", " event.user_id as user_id,\n", " event.is_oversample AS is_oversample,\n", " IF(tpe.session_id IS NOT NULL, 'comment_posted', 'no_comment_posted') AS edit_save_status,\n", " tpe.component_type AS comment_type,\n", " tpe.topic_id AS topic_id,\n", " tpe.comment_id AS comment_id,\n", " tpe.comment_parent_id AS comment_parent_id,\n", " event.user_editcount AS experience_level\n", "FROM event.editattemptstep eas\n", "LEFT JOIN \n", " event.mediawiki_talk_page_edit tpe\n", " ON event.editing_session_id = tpe.session_id\n", " AND wiki = tpe.`database`\n", " AND tpe.Year = 2022\n", " AND ((tpe.month = 06 AND tpe.day >= 02) OR (tpe.month = 07 and tpe.day <= 31))\n", "WHERE\n", "-- AB test timline\n", " eas.Year = 2022\n", " AND ((eas.month = 06 AND eas.day >= 02) OR (eas.month = 07 and eas.day <= 31))\n", " -- remove bots\n", " AND useragent.is_bot = false\n", "-- review all talk namespaces\n", " AND event.page_ns % 2 = 1\n", "-- only test events\n", " AND event.bucket in ('test', 'control')\n", " AND event.platform = 'desktop'\n", " AND event.action = 'init'\n", "-- review participating wikis list\n", " AND wiki IN ('amwiki', 'arzwiki', 'bnwiki', 'eswiki', 'fawiki', 'frwiki', 'hewiki', 'hiwiki', 'idwiki', 'itwiki', 'jawiki', \n", " 'kowiki', 'nlwiki', 'omwiki', 'plwiki', 'ptwiki', 'thwiki',\n", " 'ukwiki', 'viwiki','zhwiki')\n", "-- only logged in users\n", " AND event.user_id != 0 \"" ] }, { "cell_type": "code", "execution_count": 7, "id": "b3e2f22d-8551-4787-8765-f4b0ab68d446", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Don't forget to authenticate with Kerberos using kinit\n", "\n" ] } ], "source": [ "topic_events <- wmfdata::query_hive(query)" ] }, { "cell_type": "code", "execution_count": 8, "id": "5f7f560d-f15e-43b0-819f-4144b450ad91", "metadata": {}, "outputs": [], "source": [ "# Data cleaning and reformating\n", "\n", "# reformat user-id and adjust to include wiki to account for duplicate user id instances.\n", "# Users do not have the smae user_id on different wikis\n", "topic_events$user_id <-\n", " as.character(paste(topic_events$user_id, topic_events$wiki, sep =\"-\"))\n", "\n", "# divide experiene level groups\n", "topic_events <- topic_events %>%\n", " mutate(experience_group = cut(as.numeric(experience_level), \n", " breaks = c(0, 100, 500, \n", " Inf), \n", " labels = c('0-100 edits', '101-500 edits', 'over 500 edits'), include.lowest = TRUE))\n", "\n", "#clarfiy wiki names\n", "topic_events <- topic_events %>%\n", " mutate(\n", " wiki = case_when(\n", " #clarfiy participating project names\n", " wiki == 'amwiki' ~ \"Amharic Wikipedia\", \n", " wiki == 'bnwiki' ~ \"Bengali Wikipedia\", \n", " wiki == 'zhwiki' ~ \"Chinese Wikipedia\", \n", " wiki == 'nlwiki' ~ 'Dutch Wikipedia', \n", " wiki == 'arzwiki' ~ 'Egyptian Wikipedia', \n", " wiki == 'frwiki' ~ 'French Wikipedia', \n", " wiki == 'hewiki' ~ 'Hebrew Wikipedia', \n", " wiki == 'hiwiki' ~ 'Hindi Wikipedia', \n", " wiki == 'idwiki' ~ 'Indonesian Wikipedia', \n", " wiki == 'itwiki' ~ 'Italian Wikipedia', \n", " wiki == 'jawiki' ~ 'Japanese Wikipedia', \n", " wiki == 'kowiki' ~ 'Korean Wikipedia', \n", " wiki == 'omwiki' ~ 'Oromo Wikipedia', \n", " wiki == 'fawiki' ~ 'Persian Wikipedia', \n", " wiki == 'plwiki' ~ 'Polish Wikipedia', \n", " wiki == 'ptwiki' ~ 'Portuguese Wikipedia', \n", " wiki == 'eswiki' ~ 'Spanish Wikipedia', \n", " wiki == 'thwiki' ~ 'Thai Wikipedia', \n", " wiki == 'ukwiki' ~ 'Ukrainian Wikipedia', \n", " wiki == 'viwiki' ~ 'Vietnamese Wikipedia' \n", " )\n", " ) \n" ] }, { "cell_type": "markdown", "id": "aa4cc43e-65fd-426e-9503-c845eae10e9a", "metadata": {}, "source": [ "# Data exploration\n", "\n", "We first explored the numbers of talk page edit attempts posted by users in each experiment group in the AB test to understand the scale and distribution of events across all participating wikis." ] }, { "cell_type": "markdown", "id": "db9ff69e-fcc0-4638-b65d-9887286059d3", "metadata": {}, "source": [ "### Overall Talk Page Edit Attempts" ] }, { "cell_type": "code", "execution_count": 9, "id": "73ba6f6c-61c9-4cec-8da8-f6763be196f3", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 4 × 4
experiment_groupedit_save_statususersattempts
<chr><chr><int><int>
controlcomment_posted 637137349
controlno_comment_posted812031619
test comment_posted 647137216
test no_comment_posted795829682
\n" ], "text/latex": [ "A tibble: 4 × 4\n", "\\begin{tabular}{llll}\n", " experiment\\_group & edit\\_save\\_status & users & attempts\\\\\n", " & & & \\\\\n", "\\hline\n", "\t control & comment\\_posted & 6371 & 37349\\\\\n", "\t control & no\\_comment\\_posted & 8120 & 31619\\\\\n", "\t test & comment\\_posted & 6471 & 37216\\\\\n", "\t test & no\\_comment\\_posted & 7958 & 29682\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 4 × 4\n", "\n", "| experiment_group <chr> | edit_save_status <chr> | users <int> | attempts <int> |\n", "|---|---|---|---|\n", "| control | comment_posted | 6371 | 37349 |\n", "| control | no_comment_posted | 8120 | 31619 |\n", "| test | comment_posted | 6471 | 37216 |\n", "| test | no_comment_posted | 7958 | 29682 |\n", "\n" ], "text/plain": [ " experiment_group edit_save_status users attempts\n", "1 control comment_posted 6371 37349 \n", "2 control no_comment_posted 8120 31619 \n", "3 test comment_posted 6471 37216 \n", "4 test no_comment_posted 7958 29682 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "talk_page_attempts_bygroup <- topic_events %>%\n", " #filter(is_oversample == 'false') %>% #All Discussion Tool events are oversampled - removing to check balance.\n", " group_by(experiment_group, edit_save_status) %>%\n", " summarise(users = n_distinct(user_id),\n", " attempts = n_distinct(edit_attempt_id), .groups = 'drop')\n", "\n", "talk_page_attempts_bygroup" ] }, { "cell_type": "markdown", "id": "a4426ec3-3d56-4bcc-91da-c526e637f78f", "metadata": {}, "source": [ "### Talk Page Edit Attempts by Experience Group" ] }, { "cell_type": "code", "execution_count": 10, "id": "02519935-cd32-4f0d-8300-d0af9d2d24d0", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 12 × 5
experience_groupexperiment_groupedit_save_statususersattempts
<chr><chr><chr><int><int>
between 100 and 500 editscontrolcomment_posted 734 3005
between 100 and 500 editscontrolno_comment_posted 695 2110
between 100 and 500 editstest comment_posted 812 3336
between 100 and 500 editstest no_comment_posted 661 2026
over 500 edits controlcomment_posted 254327689
over 500 edits controlno_comment_posted243820412
over 500 edits test comment_posted 250326809
over 500 edits test no_comment_posted234018336
under 100 edits controlcomment_posted 3221 6655
under 100 edits controlno_comment_posted5098 9097
under 100 edits test comment_posted 3303 7071
under 100 edits test no_comment_posted5069 9320
\n" ], "text/latex": [ "A tibble: 12 × 5\n", "\\begin{tabular}{lllll}\n", " experience\\_group & experiment\\_group & edit\\_save\\_status & users & attempts\\\\\n", " & & & & \\\\\n", "\\hline\n", "\t between 100 and 500 edits & control & comment\\_posted & 734 & 3005\\\\\n", "\t between 100 and 500 edits & control & no\\_comment\\_posted & 695 & 2110\\\\\n", "\t between 100 and 500 edits & test & comment\\_posted & 812 & 3336\\\\\n", "\t between 100 and 500 edits & test & no\\_comment\\_posted & 661 & 2026\\\\\n", "\t over 500 edits & control & comment\\_posted & 2543 & 27689\\\\\n", "\t over 500 edits & control & no\\_comment\\_posted & 2438 & 20412\\\\\n", "\t over 500 edits & test & comment\\_posted & 2503 & 26809\\\\\n", "\t over 500 edits & test & no\\_comment\\_posted & 2340 & 18336\\\\\n", "\t under 100 edits & control & comment\\_posted & 3221 & 6655\\\\\n", "\t under 100 edits & control & no\\_comment\\_posted & 5098 & 9097\\\\\n", "\t under 100 edits & test & comment\\_posted & 3303 & 7071\\\\\n", "\t under 100 edits & test & no\\_comment\\_posted & 5069 & 9320\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 12 × 5\n", "\n", "| experience_group <chr> | experiment_group <chr> | edit_save_status <chr> | users <int> | attempts <int> |\n", "|---|---|---|---|---|\n", "| between 100 and 500 edits | control | comment_posted | 734 | 3005 |\n", "| between 100 and 500 edits | control | no_comment_posted | 695 | 2110 |\n", "| between 100 and 500 edits | test | comment_posted | 812 | 3336 |\n", "| between 100 and 500 edits | test | no_comment_posted | 661 | 2026 |\n", "| over 500 edits | control | comment_posted | 2543 | 27689 |\n", "| over 500 edits | control | no_comment_posted | 2438 | 20412 |\n", "| over 500 edits | test | comment_posted | 2503 | 26809 |\n", "| over 500 edits | test | no_comment_posted | 2340 | 18336 |\n", "| under 100 edits | control | comment_posted | 3221 | 6655 |\n", "| under 100 edits | control | no_comment_posted | 5098 | 9097 |\n", "| under 100 edits | test | comment_posted | 3303 | 7071 |\n", "| under 100 edits | test | no_comment_posted | 5069 | 9320 |\n", "\n" ], "text/plain": [ " experience_group experiment_group edit_save_status users attempts\n", "1 between 100 and 500 edits control comment_posted 734 3005 \n", "2 between 100 and 500 edits control no_comment_posted 695 2110 \n", "3 between 100 and 500 edits test comment_posted 812 3336 \n", "4 between 100 and 500 edits test no_comment_posted 661 2026 \n", "5 over 500 edits control comment_posted 2543 27689 \n", "6 over 500 edits control no_comment_posted 2438 20412 \n", "7 over 500 edits test comment_posted 2503 26809 \n", "8 over 500 edits test no_comment_posted 2340 18336 \n", "9 under 100 edits control comment_posted 3221 6655 \n", "10 under 100 edits control no_comment_posted 5098 9097 \n", "11 under 100 edits test comment_posted 3303 7071 \n", "12 under 100 edits test no_comment_posted 5069 9320 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "talk_page_attempts_byjunior <- topic_events %>%\n", " #filter(edit_save_status == 'comment_posted') %>%\n", " mutate(experience_group =\n", " case_when(\n", " experience_level < 100 ~ \"under 100 edits\",\n", " experience_level >=100 & experience_level <= 500 ~ \"between 100 and 500 edits\",\n", " experience_level > 500 ~ \"over 500 edits\"\n", " )) %>%\n", " group_by(experience_group, experiment_group, edit_save_status) %>%\n", " summarise(users = n_distinct(user_id),\n", " attempts = n_distinct(edit_attempt_id), .groups = 'drop')\n", "\n", "talk_page_attempts_byjunior" ] }, { "cell_type": "markdown", "id": "ebf35c52-b2a2-48b3-be54-8c72ec971a60", "metadata": {}, "source": [ "There is a roughly equivalent number of both senior and junior contributors that have posted a comment on a talk page during the duration of the AB test. In addition, there are no significant differences in the the number of comments posted between the test and control groups." ] }, { "cell_type": "markdown", "id": "15c76078-c009-4149-9d62-ec03f86af1a0", "metadata": {}, "source": [ "### Comments Posted by Wiki" ] }, { "cell_type": "code", "execution_count": 11, "id": "0389a407-fa18-4125-97ea-ba3d599f6151", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'experiment_group' (override with `.groups` argument)\n", "\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A grouped_df: 38 × 4
experiment_groupwikin_usersn_comments
<chr><chr><int><int>
controlAmharic Wikipedia 2 2
test Amharic Wikipedia 1 1
controlBengali Wikipedia 103 388
test Bengali Wikipedia 1231120
controlChinese Wikipedia 4541870
test Chinese Wikipedia 4792252
controlDutch Wikipedia 2681568
test Dutch Wikipedia 2601349
controlEgyptian Wikipedia 6 10
test Egyptian Wikipedia 9 69
controlFrench Wikipedia 13397376
test French Wikipedia 13897735
controlHebrew Wikipedia 4035818
test Hebrew Wikipedia 3654443
controlHindi Wikipedia 45 96
test Hindi Wikipedia 44 113
controlIndonesian Wikipedia 128 485
test Indonesian Wikipedia 130 608
controlItalian Wikipedia 6675953
test Italian Wikipedia 6614513
controlJapanese Wikipedia 6362853
test Japanese Wikipedia 6932717
controlKorean Wikipedia 831507
test Korean Wikipedia 991459
controlPersian Wikipedia 3071636
test Persian Wikipedia 2921716
controlPolish Wikipedia 3121352
test Polish Wikipedia 3171068
controlPortuguese Wikipedia 4161284
test Portuguese Wikipedia 4231390
controlSpanish Wikipedia 8473349
test Spanish Wikipedia 8143840
controlThai Wikipedia 38 112
test Thai Wikipedia 33 101
controlUkrainian Wikipedia 1841029
test Ukrainian Wikipedia 1841111
controlVietnamese Wikipedia 133 661
test Vietnamese Wikipedia 1551611
\n" ], "text/latex": [ "A grouped\\_df: 38 × 4\n", "\\begin{tabular}{llll}\n", " experiment\\_group & wiki & n\\_users & n\\_comments\\\\\n", " & & & \\\\\n", "\\hline\n", "\t control & Amharic Wikipedia & 2 & 2\\\\\n", "\t test & Amharic Wikipedia & 1 & 1\\\\\n", "\t control & Bengali Wikipedia & 103 & 388\\\\\n", "\t test & Bengali Wikipedia & 123 & 1120\\\\\n", "\t control & Chinese Wikipedia & 454 & 1870\\\\\n", "\t test & Chinese Wikipedia & 479 & 2252\\\\\n", "\t control & Dutch Wikipedia & 268 & 1568\\\\\n", "\t test & Dutch Wikipedia & 260 & 1349\\\\\n", "\t control & Egyptian Wikipedia & 6 & 10\\\\\n", "\t test & Egyptian Wikipedia & 9 & 69\\\\\n", "\t control & French Wikipedia & 1339 & 7376\\\\\n", "\t test & French Wikipedia & 1389 & 7735\\\\\n", "\t control & Hebrew Wikipedia & 403 & 5818\\\\\n", "\t test & Hebrew Wikipedia & 365 & 4443\\\\\n", "\t control & Hindi Wikipedia & 45 & 96\\\\\n", "\t test & Hindi Wikipedia & 44 & 113\\\\\n", "\t control & Indonesian Wikipedia & 128 & 485\\\\\n", "\t test & Indonesian Wikipedia & 130 & 608\\\\\n", "\t control & Italian Wikipedia & 667 & 5953\\\\\n", "\t test & Italian Wikipedia & 661 & 4513\\\\\n", "\t control & Japanese Wikipedia & 636 & 2853\\\\\n", "\t test & Japanese Wikipedia & 693 & 2717\\\\\n", "\t control & Korean Wikipedia & 83 & 1507\\\\\n", "\t test & Korean Wikipedia & 99 & 1459\\\\\n", "\t control & Persian Wikipedia & 307 & 1636\\\\\n", "\t test & Persian Wikipedia & 292 & 1716\\\\\n", "\t control & Polish Wikipedia & 312 & 1352\\\\\n", "\t test & Polish Wikipedia & 317 & 1068\\\\\n", "\t control & Portuguese Wikipedia & 416 & 1284\\\\\n", "\t test & Portuguese Wikipedia & 423 & 1390\\\\\n", "\t control & Spanish Wikipedia & 847 & 3349\\\\\n", "\t test & Spanish Wikipedia & 814 & 3840\\\\\n", "\t control & Thai Wikipedia & 38 & 112\\\\\n", "\t test & Thai Wikipedia & 33 & 101\\\\\n", "\t control & Ukrainian Wikipedia & 184 & 1029\\\\\n", "\t test & Ukrainian Wikipedia & 184 & 1111\\\\\n", "\t control & Vietnamese Wikipedia & 133 & 661\\\\\n", "\t test & Vietnamese Wikipedia & 155 & 1611\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A grouped_df: 38 × 4\n", "\n", "| experiment_group <chr> | wiki <chr> | n_users <int> | n_comments <int> |\n", "|---|---|---|---|\n", "| control | Amharic Wikipedia | 2 | 2 |\n", "| test | Amharic Wikipedia | 1 | 1 |\n", "| control | Bengali Wikipedia | 103 | 388 |\n", "| test | Bengali Wikipedia | 123 | 1120 |\n", "| control | Chinese Wikipedia | 454 | 1870 |\n", "| test | Chinese Wikipedia | 479 | 2252 |\n", "| control | Dutch Wikipedia | 268 | 1568 |\n", "| test | Dutch Wikipedia | 260 | 1349 |\n", "| control | Egyptian Wikipedia | 6 | 10 |\n", "| test | Egyptian Wikipedia | 9 | 69 |\n", "| control | French Wikipedia | 1339 | 7376 |\n", "| test | French Wikipedia | 1389 | 7735 |\n", "| control | Hebrew Wikipedia | 403 | 5818 |\n", "| test | Hebrew Wikipedia | 365 | 4443 |\n", "| control | Hindi Wikipedia | 45 | 96 |\n", "| test | Hindi Wikipedia | 44 | 113 |\n", "| control | Indonesian Wikipedia | 128 | 485 |\n", "| test | Indonesian Wikipedia | 130 | 608 |\n", "| control | Italian Wikipedia | 667 | 5953 |\n", "| test | Italian Wikipedia | 661 | 4513 |\n", "| control | Japanese Wikipedia | 636 | 2853 |\n", "| test | Japanese Wikipedia | 693 | 2717 |\n", "| control | Korean Wikipedia | 83 | 1507 |\n", "| test | Korean Wikipedia | 99 | 1459 |\n", "| control | Persian Wikipedia | 307 | 1636 |\n", "| test | Persian Wikipedia | 292 | 1716 |\n", "| control | Polish Wikipedia | 312 | 1352 |\n", "| test | Polish Wikipedia | 317 | 1068 |\n", "| control | Portuguese Wikipedia | 416 | 1284 |\n", "| test | Portuguese Wikipedia | 423 | 1390 |\n", "| control | Spanish Wikipedia | 847 | 3349 |\n", "| test | Spanish Wikipedia | 814 | 3840 |\n", "| control | Thai Wikipedia | 38 | 112 |\n", "| test | Thai Wikipedia | 33 | 101 |\n", "| control | Ukrainian Wikipedia | 184 | 1029 |\n", "| test | Ukrainian Wikipedia | 184 | 1111 |\n", "| control | Vietnamese Wikipedia | 133 | 661 |\n", "| test | Vietnamese Wikipedia | 155 | 1611 |\n", "\n" ], "text/plain": [ " experiment_group wiki n_users n_comments\n", "1 control Amharic Wikipedia 2 2 \n", "2 test Amharic Wikipedia 1 1 \n", "3 control Bengali Wikipedia 103 388 \n", "4 test Bengali Wikipedia 123 1120 \n", "5 control Chinese Wikipedia 454 1870 \n", "6 test Chinese Wikipedia 479 2252 \n", "7 control Dutch Wikipedia 268 1568 \n", "8 test Dutch Wikipedia 260 1349 \n", "9 control Egyptian Wikipedia 6 10 \n", "10 test Egyptian Wikipedia 9 69 \n", "11 control French Wikipedia 1339 7376 \n", "12 test French Wikipedia 1389 7735 \n", "13 control Hebrew Wikipedia 403 5818 \n", "14 test Hebrew Wikipedia 365 4443 \n", "15 control Hindi Wikipedia 45 96 \n", "16 test Hindi Wikipedia 44 113 \n", "17 control Indonesian Wikipedia 128 485 \n", "18 test Indonesian Wikipedia 130 608 \n", "19 control Italian Wikipedia 667 5953 \n", "20 test Italian Wikipedia 661 4513 \n", "21 control Japanese Wikipedia 636 2853 \n", "22 test Japanese Wikipedia 693 2717 \n", "23 control Korean Wikipedia 83 1507 \n", "24 test Korean Wikipedia 99 1459 \n", "25 control Persian Wikipedia 307 1636 \n", "26 test Persian Wikipedia 292 1716 \n", "27 control Polish Wikipedia 312 1352 \n", "28 test Polish Wikipedia 317 1068 \n", "29 control Portuguese Wikipedia 416 1284 \n", "30 test Portuguese Wikipedia 423 1390 \n", "31 control Spanish Wikipedia 847 3349 \n", "32 test Spanish Wikipedia 814 3840 \n", "33 control Thai Wikipedia 38 112 \n", "34 test Thai Wikipedia 33 101 \n", "35 control Ukrainian Wikipedia 184 1029 \n", "36 test Ukrainian Wikipedia 184 1111 \n", "37 control Vietnamese Wikipedia 133 661 \n", "38 test Vietnamese Wikipedia 155 1611 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "talk_page_comments_bywiki <- topic_events %>%\n", " filter(edit_save_status == 'comment_posted') %>%\n", " group_by(experiment_group, wiki) %>%\n", " summarise(n_users = n_distinct(user_id),\n", " n_comments = n_distinct(edit_attempt_id)) %>%\n", " arrange(wiki)\n", "\n", "talk_page_comments_bywiki" ] }, { "cell_type": "markdown", "id": "fa134cf9-e2b4-437e-916c-e0c77dc891af", "metadata": {}, "source": [ "There is not a sufficient sample of talk page comments and edits logged been made on Amharic, Egyptian, Oromo, Hindi and Thai Wikipedia during the AB test to conclude any results for these particular wikis; however, we will include them in the overall analysis." ] }, { "cell_type": "markdown", "id": "2fbcd161-5ee9-4f65-8bf2-b956de5ab73a", "metadata": {}, "source": [ "# Key Performance Indicator \n", "\n", "## Average time duration between post and response\n", "\n", "For all comments and new topics with a response, the average time duration from \"Person A\" posting on a talk page and \"Person B\" posting a response, grouped by the experience level of \"Person A\".\n", "\n", "For this analysis, I reviewed all comments posted on talk pages by users in the AB test and found the time a comment was posted in response either to comment or topic (top level comment). I then reviewed the averages of response times identifed over the course of the AB test for each test group and experience level to identify an differences. Note: We do not know if all of the users in the AB test were subscribed to the topic at the time of their comment or response but are interested in the overall impact Topic Subscriptions has on the rates at which people review responses to things they say on wiki.\n", "\n", "IDEAS FOR FURTHER INVESTIGATION:\n", "* How many of the users were actively subscribed at the time of their response? Are more Junior or Senior Contributors subscribing to comments?\n", "* What percentage of these responses are people responding to their own comment? Is it large enough to impact the data we see below.\n" ] }, { "cell_type": "code", "execution_count": 12, "id": "d421a6db-05d6-4304-ab26-257ae0898b4e", "metadata": {}, "outputs": [], "source": [ "# isolate only to comments that received a response\n", "# FixMe: Expand to include topics with responses as well\n", "\n", "query <- \"\n", "-- find all commenters and their experience level\n", "WITH comments_posted AS (\n", "SELECT\n", " ctpe.dt as comment_dt,\n", " comment_id,\n", " topic_id,\n", " `database` AS wiki,\n", " performer.user_edit_count AS experience_level\n", "FROM event.mediawiki_talk_page_edit ctpe\n", "INNER JOIN \n", " event.editattemptstep eas\n", " ON session_id = eas.event.editing_session_id \n", " AND `database` = eas.wiki \n", " AND eas.Year = 2022\n", "AND ((eas.month = 06 AND eas.day >= 02) OR (eas.month = 07 and eas.day <= 18))\n", "WHERE\n", "component_type = 'comment'\n", "AND ctpe.Year = 2022\n", "AND ((ctpe.month = 06 AND ctpe.day >= 02) OR (ctpe.month = 07 and ctpe.day <= 18))\n", "AND performer.user_id != 0\n", "AND eas.event.bucket in ('test', 'control')\n", "AND eas.useragent.is_bot = false\n", ")\n", "\n", "-- find all responses to those comments and the time they were posted\n", "SELECT\n", " cp.comment_dt,\n", " tpe.dt as response_dt,\n", " cp.comment_id,\n", " cp.topic_id,\n", " cp.experience_level,\n", " tpe.comment_parent_id AS comment_parent_id,\n", " tpe.comment_id AS response_id,\n", " event.action AS action,\n", " event.editing_session_id as edit_attempt_id,\n", " cp.wiki AS wiki,\n", " tpe.component_type AS response_type,\n", " event.bucket AS experiment_group,\n", " event.user_id as user_id\n", "FROM event.mediawiki_talk_page_edit tpe\n", "INNER JOIN \n", " event.editattemptstep eas\n", " ON tpe.session_id = eas.event.editing_session_id \n", " AND tpe.`database` = eas.wiki \n", " AND eas.Year = 2022\n", " AND ((eas.month = 06 AND eas.day >= 02) OR (eas.month = 07 and eas.day <= 18))\n", "INNER JOIN comments_posted cp\n", "ON (tpe.comment_parent_id = cp.comment_id OR tpe.comment_parent_id = cp.topic_id) --confirms reponse to topic or comment\n", "AND tpe.`database` = cp.wiki\n", "WHERE\n", "-- AB test timline\n", " tpe.Year = 2022\n", " AND ((tpe.month = 06 AND tpe.day >= 02) OR (tpe.month = 07 and tpe.day <= 18))\n", " -- remove bots\n", " AND eas.useragent.is_bot = false\n", "-- review all talk namespaces\n", " AND event.page_ns % 2 = 1\n", " AND (tpe.component_type = 'response' OR tpe.component_type = 'comment')\n", " AND tpe.dt > cp.comment_dt -- response occured after post\n", " AND event.action = 'saveSuccess' \n", "-- only test events\n", " AND eas.event.bucket in ('test', 'control')\n", " AND event.platform = 'desktop'\n", "-- review participating wikis list\n", " AND cp.wiki IN ('amwiki', 'arzwiki', 'bnwiki', 'eswiki', 'fawiki', 'frwiki', 'hewiki', 'hiwiki', 'idwiki', 'itwiki', 'jawiki', \n", " 'kowiki', 'nlwiki', 'omwiki', 'plwiki', 'ptwiki', 'thwiki',\n", " 'ukwiki', 'viwiki','zhwiki')\n", "-- only logged in users\n", " AND tpe.performer.user_id != 0\n", "\"\n" ] }, { "cell_type": "code", "execution_count": 13, "id": "5d27364e-6255-4d69-921d-1686dbea7008", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Don't forget to authenticate with Kerberos using kinit\n", "\n" ] } ], "source": [ "topic_response_data <- wmfdata::query_hive(query)" ] }, { "cell_type": "code", "execution_count": 14, "id": "6dbd7d2f-6840-468e-89a0-a58fa6e4461e", "metadata": {}, "outputs": [], "source": [ "# Reformat dates\n", "\n", "topic_response_data$response_dt <- as.POSIXct(topic_response_data$response_dt, format = \"%Y-%m-%dT%H:%M:%OSZ\", tz = \"UTC\")\n", "topic_response_data$comment_dt <- as.POSIXct(topic_response_data$comment_dt, format = \"%Y-%m-%dT%H:%M:%OSZ\", tz = \"UTC\")" ] }, { "cell_type": "code", "execution_count": 15, "id": "4ba43565-472e-4144-bd3c-00bcf9170a74", "metadata": {}, "outputs": [], "source": [ "# Data cleaning and refactoring\n", "\n", "#set factor levels with correct baselines\n", "topic_response_data$experiment_group <-\n", " factor(\n", " topic_response_data$experiment_group,\n", " levels = c(\"control\", \"test\"),\n", " labels = c(\"control\", \"test\")\n", " )\n", "\n", "\n", "# reformat user-id and adjust to include wiki to account for duplicate user id instances.\n", "# Users do not have the smae user_id on different wikis\n", "topic_response_data$user_id <-\n", " as.character(paste(topic_response_data$user_id, topic_response_data$wiki, sep =\"-\"))\n", "\n", "\n", "#clarfiy wiki names\n", "topic_response_data <- topic_response_data %>%\n", " mutate(\n", " wiki = case_when(\n", " #clarfiy participating project names\n", " wiki == 'amwiki' ~ \"Amharic Wikipedia\", \n", " wiki == 'bnwiki' ~ \"Bengali Wikipedia\", \n", " wiki == 'zhwiki' ~ \"Chinese Wikipedia\", \n", " wiki == 'nlwiki' ~ 'Dutch Wikipedia', \n", " wiki == 'arzwiki' ~ 'Egyptian Wikipedia', \n", " wiki == 'frwiki' ~ 'French Wikipedia', \n", " wiki == 'hewiki' ~ 'Hebrew Wikipedia', \n", " wiki == 'hiwiki' ~ 'Hindi Wikipedia', \n", " wiki == 'idwiki' ~ 'Indonesian Wikipedia', \n", " wiki == 'itwiki' ~ 'Italian Wikipedia', \n", " wiki == 'jawiki' ~ 'Japanese Wikipedia', \n", " wiki == 'kowiki' ~ 'Korean Wikipedia', \n", " wiki == 'omwiki' ~ 'Oromo Wikipedia', \n", " wiki == 'fawiki' ~ 'Persian Wikipedia', \n", " wiki == 'plwiki' ~ 'Polish Wikipedia', \n", " wiki == 'ptwiki' ~ 'Portuguese Wikipedia', \n", " wiki == 'eswiki' ~ 'Spanish Wikipedia', \n", " wiki == 'thwiki' ~ 'Thai Wikipedia', \n", " wiki == 'ukwiki' ~ 'Ukrainian Wikipedia', \n", " wiki == 'viwiki' ~ 'Vietnamese Wikipedia' \n", " )\n", " ) \n", "\n" ] }, { "cell_type": "code", "execution_count": 16, "id": "0337cbb5-df65-4055-a215-a8939a257bd6", "metadata": {}, "outputs": [], "source": [ "# divide and define experience level groups\n", "\n", "topic_response_data_exp <- topic_response_data %>%\n", " mutate(experience_group = cut(as.numeric(experience_level), \n", " breaks = c(0, 100, 500, \n", " Inf), \n", " labels = c('0-100 edits', '101-500 edits', 'over 500 edits'), include.lowest = TRUE))\n" ] }, { "cell_type": "markdown", "id": "f2149713-a7ba-43e5-ad8c-22b9a4a321a0", "metadata": {}, "source": [ "## Distribution of response time\n", "\n", "We first reviewed the distibution of response times. Since both the test and control data sets are highly skewed with most response times occuring under 1 hour, I'd recommend looking at the median instead of the mean response time to identify the typical response time of a user." ] }, { "cell_type": "code", "execution_count": 103, "id": "fb860005-dc57-40d7-8c79-ed2bc15e2a28", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A data.frame: 6 × 14
comment_dtresponse_dtcomment_idtopic_idexperience_levelcomment_parent_idresponse_idactionedit_attempt_idwikiresponse_typeexperiment_groupuser_idexperience_group
<dttm><dttm><chr><chr><int><chr><chr><chr><chr><chr><chr><fct><chr><fct>
12022-07-13 23:18:592022-07-13 23:34:48c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাh-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-2022071315190055h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাsaveSuccess371147d67246052cf9dbBengali Wikipediacommenttest380310-bnwiki0-100 edits
22022-07-13 23:18:592022-07-13 23:34:48c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাh-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-2022071315190055h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাsaveSuccess371147d67246052cf9dbBengali Wikipediacommenttest380310-bnwiki0-100 edits
32022-07-13 23:18:592022-07-13 23:34:48c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাh-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-2022071315190055h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাsaveSuccess371147d67246052cf9dbBengali Wikipediacommenttest380310-bnwiki0-100 edits
42022-07-13 23:18:592022-07-13 23:34:48c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাh-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-2022071315190055h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাsaveSuccess371147d67246052cf9dbBengali Wikipediacommenttest380310-bnwiki0-100 edits
52022-07-13 23:18:592022-07-13 23:34:48c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাh-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-2022071315190055h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাsaveSuccess371147d67246052cf9dbBengali Wikipediacommenttest380310-bnwiki0-100 edits
62022-07-13 23:18:592022-07-13 23:34:48c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাh-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-2022071315190055h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলাsaveSuccess371147d67246052cf9dbBengali Wikipediacommenttest380310-bnwiki0-100 edits
\n" ], "text/latex": [ "A data.frame: 6 × 14\n", "\\begin{tabular}{r|llllllllllllll}\n", " & comment\\_dt & response\\_dt & comment\\_id & topic\\_id & experience\\_level & comment\\_parent\\_id & response\\_id & action & edit\\_attempt\\_id & wiki & response\\_type & experiment\\_group & user\\_id & experience\\_group\\\\\n", " & & & & & & & & & & & & & & \\\\\n", "\\hline\n", "\t1 & 2022-07-13 23:18:59 & 2022-07-13 23:34:48 & c-J.\\_Modak-20220713231800-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & 55 & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & c-J.\\_Modak-20220713233400-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & saveSuccess & 371147d67246052cf9db & Bengali Wikipedia & comment & test & 380310-bnwiki & 0-100 edits\\\\\n", "\t2 & 2022-07-13 23:18:59 & 2022-07-13 23:34:48 & c-J.\\_Modak-20220713231800-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & 55 & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & c-J.\\_Modak-20220713233400-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & saveSuccess & 371147d67246052cf9db & Bengali Wikipedia & comment & test & 380310-bnwiki & 0-100 edits\\\\\n", "\t3 & 2022-07-13 23:18:59 & 2022-07-13 23:34:48 & c-J.\\_Modak-20220713231800-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & 55 & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & c-J.\\_Modak-20220713233400-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & saveSuccess & 371147d67246052cf9db & Bengali Wikipedia & comment & test & 380310-bnwiki & 0-100 edits\\\\\n", "\t4 & 2022-07-13 23:18:59 & 2022-07-13 23:34:48 & c-J.\\_Modak-20220713231800-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & 55 & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & c-J.\\_Modak-20220713233400-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & saveSuccess & 371147d67246052cf9db & Bengali Wikipedia & comment & test & 380310-bnwiki & 0-100 edits\\\\\n", "\t5 & 2022-07-13 23:18:59 & 2022-07-13 23:34:48 & c-J.\\_Modak-20220713231800-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & 55 & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & c-J.\\_Modak-20220713233400-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & saveSuccess & 371147d67246052cf9db & Bengali Wikipedia & comment & test & 380310-bnwiki & 0-100 edits\\\\\n", "\t6 & 2022-07-13 23:18:59 & 2022-07-13 23:34:48 & c-J.\\_Modak-20220713231800-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & 55 & h-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা-20220713151900 & c-J.\\_Modak-20220713233400-Md.Farhan\\_Mahmud-এর\\_প্রশ্ন\\_(১৫:১৯,\\_১৩\\_জুলা & saveSuccess & 371147d67246052cf9db & Bengali Wikipedia & comment & test & 380310-bnwiki & 0-100 edits\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A data.frame: 6 × 14\n", "\n", "| | comment_dt <dttm> | response_dt <dttm> | comment_id <chr> | topic_id <chr> | experience_level <int> | comment_parent_id <chr> | response_id <chr> | action <chr> | edit_attempt_id <chr> | wiki <chr> | response_type <chr> | experiment_group <fct> | user_id <chr> | experience_group <fct> |\n", "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n", "| 1 | 2022-07-13 23:18:59 | 2022-07-13 23:34:48 | c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | 55 | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | saveSuccess | 371147d67246052cf9db | Bengali Wikipedia | comment | test | 380310-bnwiki | 0-100 edits |\n", "| 2 | 2022-07-13 23:18:59 | 2022-07-13 23:34:48 | c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | 55 | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | saveSuccess | 371147d67246052cf9db | Bengali Wikipedia | comment | test | 380310-bnwiki | 0-100 edits |\n", "| 3 | 2022-07-13 23:18:59 | 2022-07-13 23:34:48 | c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | 55 | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | saveSuccess | 371147d67246052cf9db | Bengali Wikipedia | comment | test | 380310-bnwiki | 0-100 edits |\n", "| 4 | 2022-07-13 23:18:59 | 2022-07-13 23:34:48 | c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | 55 | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | saveSuccess | 371147d67246052cf9db | Bengali Wikipedia | comment | test | 380310-bnwiki | 0-100 edits |\n", "| 5 | 2022-07-13 23:18:59 | 2022-07-13 23:34:48 | c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | 55 | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | saveSuccess | 371147d67246052cf9db | Bengali Wikipedia | comment | test | 380310-bnwiki | 0-100 edits |\n", "| 6 | 2022-07-13 23:18:59 | 2022-07-13 23:34:48 | c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | 55 | h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 | c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা | saveSuccess | 371147d67246052cf9db | Bengali Wikipedia | comment | test | 380310-bnwiki | 0-100 edits |\n", "\n" ], "text/plain": [ " comment_dt response_dt \n", "1 2022-07-13 23:18:59 2022-07-13 23:34:48\n", "2 2022-07-13 23:18:59 2022-07-13 23:34:48\n", "3 2022-07-13 23:18:59 2022-07-13 23:34:48\n", "4 2022-07-13 23:18:59 2022-07-13 23:34:48\n", "5 2022-07-13 23:18:59 2022-07-13 23:34:48\n", "6 2022-07-13 23:18:59 2022-07-13 23:34:48\n", " comment_id \n", "1 c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা\n", "2 c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা\n", "3 c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা\n", "4 c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা\n", "5 c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা\n", "6 c-J._Modak-20220713231800-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা\n", " topic_id experience_level\n", "1 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 55 \n", "2 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 55 \n", "3 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 55 \n", "4 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 55 \n", "5 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 55 \n", "6 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900 55 \n", " comment_parent_id \n", "1 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900\n", "2 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900\n", "3 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900\n", "4 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900\n", "5 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900\n", "6 h-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা-20220713151900\n", " response_id action \n", "1 c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা saveSuccess\n", "2 c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা saveSuccess\n", "3 c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা saveSuccess\n", "4 c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা saveSuccess\n", "5 c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা saveSuccess\n", "6 c-J._Modak-20220713233400-Md.Farhan_Mahmud-এর_প্রশ্ন_(১৫:১৯,_১৩_জুলা saveSuccess\n", " edit_attempt_id wiki response_type experiment_group\n", "1 371147d67246052cf9db Bengali Wikipedia comment test \n", "2 371147d67246052cf9db Bengali Wikipedia comment test \n", "3 371147d67246052cf9db Bengali Wikipedia comment test \n", "4 371147d67246052cf9db Bengali Wikipedia comment test \n", "5 371147d67246052cf9db Bengali Wikipedia comment test \n", "6 371147d67246052cf9db Bengali Wikipedia comment test \n", " user_id experience_group\n", "1 380310-bnwiki 0-100 edits \n", "2 380310-bnwiki 0-100 edits \n", "3 380310-bnwiki 0-100 edits \n", "4 380310-bnwiki 0-100 edits \n", "5 380310-bnwiki 0-100 edits \n", "6 380310-bnwiki 0-100 edits " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "head(topic_response_data_exp)" ] }, { "cell_type": "code", "execution_count": 118, "id": "f1c0b627-c32a-4003-96d7-e509d8d8463a", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'comment_id', 'response_dt', 'comment_dt', 'experiment_group' (override with `.groups` argument)\n", "\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAACWAAAASwCAIAAADwxubWAAAACXBIWXMAABJ0AAASdAHeZh94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\nTkSuQmCC", "text/plain": [ "plot without title" ] }, "metadata": { "image/png": { "height": 600, "width": 1200 } }, "output_type": "display_data" } ], "source": [ "# Create histogram\n", "\n", "response_histogram <- topic_response_data_exp %>%\n", " group_by(comment_id, response_dt, comment_dt, experiment_group) %>%\n", " summarise(response_time = difftime(response_dt, comment_dt, units = \"secs\")) %>% \n", " #filter(response_time < 3600) %>% #remove significant outliers to help more clearly see distribution of majority\n", " ggplot(aes(x=response_time/3600, fill = experiment_group)) + #round to nearest hour\n", " geom_histogram(color = \"black\", binwidth = 50, position = 'dodge') +\n", " scale_x_continuous(labels = scales::comma, breaks=seq(0,800,50)) +\n", " labs (title = \"Distribution of response times to comments posted by users in the AB test\",\n", " y = \"Number of responses\",\n", " x= \"Response time (hours)\") + \n", " scale_fill_manual(values= c(\"#999999\", \"steelblue2\"), name = \"Experiment Group\", labels = c(\"Control (Topic subscriptions disabled)\", \"Test (Topic subscriptions enabled)\")) +\n", " theme(\n", " panel.grid.minor = element_blank(),\n", " panel.background = element_blank(),\n", " plot.title = element_text(hjust = 0.5),\n", " text = element_text(size=20),\n", " legend.position=\"bottom\",\n", " axis.line = element_line(colour = \"black\")) \n", "\n", "response_histogram\n", "\n", "ggsave(\"Figures/response_time_histogram.png\",response_histogram, width = 16, height = 11, units = \"in\", dpi = 300)" ] }, { "cell_type": "markdown", "id": "02561279-522c-43bc-a058-d74d86f7ae57", "metadata": {}, "source": [ "### How many responses are provided under or over 10 days?" ] }, { "cell_type": "code", "execution_count": 107, "id": "51377f63-7a68-4aca-820e-bef0f0d515b2", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 4 × 3
experiment_groupresponse_time_groupn_responses
<fct><chr><int>
controllong 84
controlshort1070
test long 3
test short 736
\n" ], "text/latex": [ "A tibble: 4 × 3\n", "\\begin{tabular}{lll}\n", " experiment\\_group & response\\_time\\_group & n\\_responses\\\\\n", " & & \\\\\n", "\\hline\n", "\t control & long & 84\\\\\n", "\t control & short & 1070\\\\\n", "\t test & long & 3\\\\\n", "\t test & short & 736\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 4 × 3\n", "\n", "| experiment_group <fct> | response_time_group <chr> | n_responses <int> |\n", "|---|---|---|\n", "| control | long | 84 |\n", "| control | short | 1070 |\n", "| test | long | 3 |\n", "| test | short | 736 |\n", "\n" ], "text/plain": [ " experiment_group response_time_group n_responses\n", "1 control long 84 \n", "2 control short 1070 \n", "3 test long 3 \n", "4 test short 736 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "length_response_times <- topic_response_data_exp %>%\n", " mutate(response_time = difftime(response_dt, comment_dt, units = \"secs\"),\n", " response_time=response_time/3600,\n", " response_time_group = ifelse(response_time > 240, \"long\", \"short\")) %>% \n", " group_by(experiment_group, response_time_group) %>%\n", " summarise(n_responses = n(), .groups = 'drop')\n", "\n", "length_response_times " ] }, { "cell_type": "markdown", "id": "09ef4f72-22db-4f1b-ac7e-972f6c535e07", "metadata": {}, "source": [ "There are fewer outliers (long response times) in the test group. \n", "\n", "Among people who had access to Topic Subscriptions during the A/B test, 0.4% of responses were published >10 days after the initial comment was posted\n", "Among people who did NOT have access to Topic Subscriptions during the A/B test, 7.3% of responses were published >10 days after the initial comment was posted\n" ] }, { "cell_type": "markdown", "id": "3b4e1f38-4ec6-43cb-84fd-ca32d4c75115", "metadata": {}, "source": [ "## Overall across both test groups" ] }, { "cell_type": "code", "execution_count": 19, "id": "bc40cfd6-ae42-4b00-b6ad-11dc3a94c49b", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\n", "
A tibble: 2 × 3
experiment_groupmedian_response_timemean_response_time
<fct><drtn><drtn>
control90 mins2920 mins
test 39 mins1861 mins
\n" ], "text/latex": [ "A tibble: 2 × 3\n", "\\begin{tabular}{lll}\n", " experiment\\_group & median\\_response\\_time & mean\\_response\\_time\\\\\n", " & & \\\\\n", "\\hline\n", "\t control & 90 mins & 2920 mins\\\\\n", "\t test & 39 mins & 1861 mins\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 2 × 3\n", "\n", "| experiment_group <fct> | median_response_time <drtn> | mean_response_time <drtn> |\n", "|---|---|---|\n", "| control | 90 mins | 2920 mins |\n", "| test | 39 mins | 1861 mins |\n", "\n" ], "text/plain": [ " experiment_group median_response_time mean_response_time\n", "1 control 90 mins 2920 mins \n", "2 test 39 mins 1861 mins " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# find the average time difference\n", "\n", "avg_time_response_overall <- topic_response_data_exp %>%\n", " mutate(response_time = difftime(response_dt, comment_dt, units = \"mins\")) %>% ## add column to show response time\n", " group_by(experiment_group) %>%\n", " summarise(median_response_time = round(median(response_time), 0),\n", " mean_response_time = round(mean(response_time), 0), .groups = 'drop'\n", " ) \n", " \n", "\n", "avg_time_response_overall" ] }, { "cell_type": "markdown", "id": "462b910a-34d9-45d0-87f8-45c262ce2b4c", "metadata": {}, "source": [ "#### Review of Percentiles" ] }, { "cell_type": "code", "execution_count": 20, "id": "107a025a-e3cf-4ab0-913e-e3301fef122f", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'experiment_group' (override with `.groups` argument)\n", "\n" ] } ], "source": [ "avg_time_response_percentiles <- topic_response_data_exp %>%\n", " mutate(response_time = difftime(response_dt, comment_dt, units = \"mins\")) %>% ## add column to show response time\n", " group_by(experiment_group) %>%\n", " summarise(quantile = scales::percent(c(0.25, 0.5, 0.75)),\n", " response_time = round(quantile(response_time, c(0.25, 0.5, 0.75)), 0) )%>%\n", " pivot_wider(names_from = quantile, values_from = response_time)\n", " \n" ] }, { "cell_type": "code", "execution_count": 21, "id": "baca9884-3c3a-46cc-818a-866f01d7e059", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\n", "
A tibble: 2 × 6
experiment_groupmedian_response_timemean_response_time25%50%75%
<fct><drtn><drtn><drtn><drtn><drtn>
control90 mins2920 mins6 mins90 mins2713 mins
test 39 mins1861 mins2 mins39 mins2620 mins
\n" ], "text/latex": [ "A tibble: 2 × 6\n", "\\begin{tabular}{llllll}\n", " experiment\\_group & median\\_response\\_time & mean\\_response\\_time & 25\\% & 50\\% & 75\\%\\\\\n", " & & & & & \\\\\n", "\\hline\n", "\t control & 90 mins & 2920 mins & 6 mins & 90 mins & 2713 mins\\\\\n", "\t test & 39 mins & 1861 mins & 2 mins & 39 mins & 2620 mins\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 2 × 6\n", "\n", "| experiment_group <fct> | median_response_time <drtn> | mean_response_time <drtn> | 25% <drtn> | 50% <drtn> | 75% <drtn> |\n", "|---|---|---|---|---|---|\n", "| control | 90 mins | 2920 mins | 6 mins | 90 mins | 2713 mins |\n", "| test | 39 mins | 1861 mins | 2 mins | 39 mins | 2620 mins |\n", "\n" ], "text/plain": [ " experiment_group median_response_time mean_response_time 25% 50% \n", "1 control 90 mins 2920 mins 6 mins 90 mins\n", "2 test 39 mins 1861 mins 2 mins 39 mins\n", " 75% \n", "1 2713 mins\n", "2 2620 mins" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# join the two data sets\n", "# find percent reponse rate\n", "response_time_stats <- inner_join(avg_time_response_overall, avg_time_response_percentiles, by = c(\"experiment_group\")) \n", "response_time_stats \n" ] }, { "cell_type": "markdown", "id": "b54bf8f1-a0d0-4520-aabf-1432010ed6e5", "metadata": {}, "source": [ "The average is heavily influenced by the 90th percentile, the tail, rather than the majority of the response times. In this case, 75% of response times are complete in under 3000 minutes. \n", "\n", "The 50% percentile indicates that half of the response times were below and half were above this value.Based on this, I recommend we use the median (50th) percentile as a better indicator of the typical response time in the test." ] }, { "cell_type": "code", "execution_count": 22, "id": "d62cebbf-6989-4ac2-ac58-e707612fe2c6", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Summary of response times across all participating Wikipedias
Experiment Group1Median response time (minutes)2Mean response time (minutes)3
control902920
test391861
\n", "

\n", " \n", " 1\n", " \n", " \n", " Test: Topic subscriptions enabled by default; Control: Topic subscriptions not enabled\n", "
\n", "

\n", "

\n", " \n", " 2\n", " \n", " \n", " Defined as the midpoint of identified time durations from Person A posting on a talk page and Person B posting a response\n", "
\n", "

\n", "

\n", " \n", " 3\n", " \n", " \n", " Defined as the average time duration from Person A posting on a talk page and Person B posting a response\"\n", "
\n", "

\n", "
\n", "\n", "\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Create table of completion rate\n", "avg_time_response_overall_table <- avg_time_response_overall%>%\n", " gt() %>%\n", " tab_header(\n", " title = \"Summary of response times across all participating Wikipedias\",\n", " ) %>%\n", " cols_label(\n", " experiment_group = \"Experiment Group\",\n", " median_response_time = \"Median response time (minutes)\",\n", " mean_response_time = \"Mean response time (minutes)\"\n", " ) %>%\n", " tab_footnote(\n", " footnote = \"Defined as the midpoint of identified time durations from Person A posting on a talk page and Person B posting a response\",\n", " locations = cells_column_labels(\n", " columns = \"median_response_time\"\n", " )\n", " ) %>%\n", " tab_footnote(\n", " footnote = 'Test: Topic subscriptions enabled by default; Control: Topic subscriptions not enabled',\n", " locations = cells_column_labels(\n", " columns = 'experiment_group')\n", " ) %>%\n", " tab_footnote(\n", " footnote = 'Defined as the average time duration from Person A posting on a talk page and Person B posting a response\"',\n", " locations = cells_column_labels(\n", " columns = 'mean_response_time')\n", " ) %>%\n", " gtsave(\n", " \"avg_time_response_overall_table.html\", inline_css = TRUE)\n", "\n", "IRdisplay::display_html(data = avg_time_response_overall_table , file = \"avg_time_response_overall_table.html\")" ] }, { "cell_type": "code", "execution_count": 122, "id": "59b8cbf3-ad54-4799-8888-96fe965d6da3", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAACWAAAASwCAIAAADwxubWAAAACXBIWXMAABJ0AAASdAHeZh94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", "text/plain": [ "plot without title" ] }, "metadata": { "image/png": { "height": 600, "width": 1200 } }, "output_type": "display_data" } ], "source": [ "p <- avg_time_response_overall %>%\n", " ggplot(aes(x= experiment_group, y = median_response_time, fill = experiment_group)) +\n", " geom_col(position = 'dodge') +\n", " geom_text(aes(label = paste(median_response_time, \"min\"), fontface=2), vjust=1.2, size = 8, color = \"white\") +\n", " scale_y_continuous() +\n", " scale_x_discrete(labels = c(\"Control (Topic subscriptions disabled)\", \"Test (Topic subscriptions enabled)\")) +\n", " labs (y = \"Median response time (minutes) \",\n", " x = \"Experiment group\",\n", " title = \"Median response times by users in AB test\",\n", " caption = \"Defined as the median time duration from Person A posting on a talk page and Person B posting a response\") +\n", " scale_fill_manual(values= c(\"#999999\", \"steelblue2\")) +\n", " theme(\n", " panel.grid.minor = element_blank(),\n", " panel.background = element_blank(),\n", " plot.title = element_text(hjust = 0.5),\n", " text = element_text(size=20),\n", " legend.position= \"none\",\n", " axis.line = element_line(colour = \"black\")) \n", " \n", "\n", "p\n", "ggsave(\"Figures/median_time_response_overall.png\", p, width = 16, height = 12, units = \"in\", dpi = 300)" ] }, { "cell_type": "markdown", "id": "0d9ddfec-1de1-4417-92e3-3d2c93b97889", "metadata": {}, "source": [ "There was 51 minute decrease (57% decrease) in the median response time for the test group compared to the control group." ] }, { "cell_type": "markdown", "id": "28720cac-2cba-408a-9c9e-18f9518a2e11", "metadata": {}, "source": [ "### By experience level" ] }, { "cell_type": "code", "execution_count": 29, "id": "f457b1a7-5587-4fcd-97c7-86aedc22405e", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'experiment_group' (override with `.groups` argument)\n", "\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A grouped_df: 6 × 4
experiment_groupexperience_groupmedian_response_time_minutesmean_response_time_minutes
<fct><fct><int><int>
control0-100 edits 62 249
test 0-100 edits 3 893
control101-500 edits 347532
test 101-500 edits 551421
controlover 500 edits 902240
test over 500 edits3112391
\n" ], "text/latex": [ "A grouped\\_df: 6 × 4\n", "\\begin{tabular}{llll}\n", " experiment\\_group & experience\\_group & median\\_response\\_time\\_minutes & mean\\_response\\_time\\_minutes\\\\\n", " & & & \\\\\n", "\\hline\n", "\t control & 0-100 edits & 62 & 249\\\\\n", "\t test & 0-100 edits & 3 & 893\\\\\n", "\t control & 101-500 edits & 34 & 7532\\\\\n", "\t test & 101-500 edits & 55 & 1421\\\\\n", "\t control & over 500 edits & 90 & 2240\\\\\n", "\t test & over 500 edits & 311 & 2391\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A grouped_df: 6 × 4\n", "\n", "| experiment_group <fct> | experience_group <fct> | median_response_time_minutes <int> | mean_response_time_minutes <int> |\n", "|---|---|---|---|\n", "| control | 0-100 edits | 62 | 249 |\n", "| test | 0-100 edits | 3 | 893 |\n", "| control | 101-500 edits | 34 | 7532 |\n", "| test | 101-500 edits | 55 | 1421 |\n", "| control | over 500 edits | 90 | 2240 |\n", "| test | over 500 edits | 311 | 2391 |\n", "\n" ], "text/plain": [ " experiment_group experience_group median_response_time_minutes\n", "1 control 0-100 edits 62 \n", "2 test 0-100 edits 3 \n", "3 control 101-500 edits 34 \n", "4 test 101-500 edits 55 \n", "5 control over 500 edits 90 \n", "6 test over 500 edits 311 \n", " mean_response_time_minutes\n", "1 249 \n", "2 893 \n", "3 7532 \n", "4 1421 \n", "5 2240 \n", "6 2391 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# find the average time difference by experience level\n", "\n", "avg_time_response_byexp <- topic_response_data_exp %>%\n", " mutate(response_time = difftime(response_dt, comment_dt, units = \"mins\")) %>% ## add column to show response time\n", " group_by(experiment_group, experience_group) %>%\n", " summarise(median_response_time_minutes = as.integer(median(response_time)),\n", " mean_response_time_minutes = as.integer(mean(response_time))) %>%\n", " arrange(experience_group)\n", "\n", "avg_time_response_byexp" ] }, { "cell_type": "code", "execution_count": 30, "id": "f0a7aab9-a696-426f-953b-f5b0a87dd1ea", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAACWAAAASwCAIAAADwxubWAAAACXBIWXMAABJ0AAASdAHeZh94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\nRU5ErkJggg==", "text/plain": [ "plot without title" ] }, "metadata": { "image/png": { "height": 600, "width": 1200 } }, "output_type": "display_data" } ], "source": [ "# Plot edit completion rates for each user on each wiki \n", "\n", "p <- avg_time_response_byexp %>%\n", " ggplot(aes(x= experiment_group, y = median_response_time_minutes, fill = experiment_group)) +\n", " geom_col(position = 'dodge') +\n", " geom_text(aes(label = paste(median_response_time_minutes, \"mins\"), fontface=2), vjust=1.2, size = 8, color = \"white\") +\n", " facet_wrap(~ experience_group, scales = \"free_y\") +\n", " scale_y_continuous() +\n", " labs (y = \"Median response time in minutes\",\n", " title = \"Median response time by experience level \\n across all participating Wikipedias\"\n", " )+\n", " scale_fill_manual(values= c(\"#999999\", \"steelblue2\"), name = \"Experiment Group\", labels = c(\"Control\", \"Test\")) +\n", " theme(\n", " panel.grid.minor = element_blank(),\n", " panel.background = element_blank(),\n", " plot.title = element_text(hjust = 0.5),\n", " text = element_text(size=16),\n", " legend.position=\"bottom\",\n", " axis.text.x = element_blank(),\n", " axis.title.x=element_blank(),\n", " axis.line = element_line(colour = \"black\")) \n", "\n", "p \n", "ggsave(\"Figures/avg_time_response_byexp.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)" ] }, { "cell_type": "markdown", "id": "ac8ec58d-9b10-43c6-adc2-56770c4e6f39", "metadata": {}, "source": [ "When we split by experience group, the results are much more varied. We see a significant decrease (-95%) in median response times to Junior Contributors that posted a comment in the test group but an increase for Senior Contributors that posted a comment. Differing trends are seen for averages. \n", "\n", "Further investigation is likely needed to clarify these results. " ] }, { "cell_type": "markdown", "id": "f2946acd-73e9-4c27-9b0c-f272c3aa62a5", "metadata": {}, "source": [ "### By Wiki" ] }, { "cell_type": "code", "execution_count": 45, "id": "fdaa2853-ff7e-4cb4-bd19-0800ccfc380f", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'experiment_group' (override with `.groups` argument)\n", "\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A grouped_df: 18 × 4
experiment_groupwikimedian_response_time_minutesmean_response_time_minutes
<fct><chr><int><int>
controlChinese Wikipedia 49535003
test Chinese Wikipedia 50906378
controlFrench Wikipedia 641023
test French Wikipedia 553167
controlHebrew Wikipedia 23159
test Hebrew Wikipedia 6761600
controlItalian Wikipedia 5 12
test Italian Wikipedia 28201549
controlJapanese Wikipedia 14014668
test Japanese Wikipedia 2841534
controlPersian Wikipedia 1 2
test Persian Wikipedia 18 643
controlPortuguese Wikipedia 4 4
test Portuguese Wikipedia 993 797
controlSpanish Wikipedia 1992689
test Spanish Wikipedia 9 9
controlVietnamese Wikipedia 62 62
test Vietnamese Wikipedia 1 23
\n" ], "text/latex": [ "A grouped\\_df: 18 × 4\n", "\\begin{tabular}{llll}\n", " experiment\\_group & wiki & median\\_response\\_time\\_minutes & mean\\_response\\_time\\_minutes\\\\\n", " & & & \\\\\n", "\\hline\n", "\t control & Chinese Wikipedia & 4953 & 5003\\\\\n", "\t test & Chinese Wikipedia & 5090 & 6378\\\\\n", "\t control & French Wikipedia & 64 & 1023\\\\\n", "\t test & French Wikipedia & 55 & 3167\\\\\n", "\t control & Hebrew Wikipedia & 2 & 3159\\\\\n", "\t test & Hebrew Wikipedia & 676 & 1600\\\\\n", "\t control & Italian Wikipedia & 5 & 12\\\\\n", "\t test & Italian Wikipedia & 2820 & 1549\\\\\n", "\t control & Japanese Wikipedia & 1401 & 4668\\\\\n", "\t test & Japanese Wikipedia & 284 & 1534\\\\\n", "\t control & Persian Wikipedia & 1 & 2\\\\\n", "\t test & Persian Wikipedia & 18 & 643\\\\\n", "\t control & Portuguese Wikipedia & 4 & 4\\\\\n", "\t test & Portuguese Wikipedia & 993 & 797\\\\\n", "\t control & Spanish Wikipedia & 199 & 2689\\\\\n", "\t test & Spanish Wikipedia & 9 & 9\\\\\n", "\t control & Vietnamese Wikipedia & 62 & 62\\\\\n", "\t test & Vietnamese Wikipedia & 1 & 23\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A grouped_df: 18 × 4\n", "\n", "| experiment_group <fct> | wiki <chr> | median_response_time_minutes <int> | mean_response_time_minutes <int> |\n", "|---|---|---|---|\n", "| control | Chinese Wikipedia | 4953 | 5003 |\n", "| test | Chinese Wikipedia | 5090 | 6378 |\n", "| control | French Wikipedia | 64 | 1023 |\n", "| test | French Wikipedia | 55 | 3167 |\n", "| control | Hebrew Wikipedia | 2 | 3159 |\n", "| test | Hebrew Wikipedia | 676 | 1600 |\n", "| control | Italian Wikipedia | 5 | 12 |\n", "| test | Italian Wikipedia | 2820 | 1549 |\n", "| control | Japanese Wikipedia | 1401 | 4668 |\n", "| test | Japanese Wikipedia | 284 | 1534 |\n", "| control | Persian Wikipedia | 1 | 2 |\n", "| test | Persian Wikipedia | 18 | 643 |\n", "| control | Portuguese Wikipedia | 4 | 4 |\n", "| test | Portuguese Wikipedia | 993 | 797 |\n", "| control | Spanish Wikipedia | 199 | 2689 |\n", "| test | Spanish Wikipedia | 9 | 9 |\n", "| control | Vietnamese Wikipedia | 62 | 62 |\n", "| test | Vietnamese Wikipedia | 1 | 23 |\n", "\n" ], "text/plain": [ " experiment_group wiki median_response_time_minutes\n", "1 control Chinese Wikipedia 4953 \n", "2 test Chinese Wikipedia 5090 \n", "3 control French Wikipedia 64 \n", "4 test French Wikipedia 55 \n", "5 control Hebrew Wikipedia 2 \n", "6 test Hebrew Wikipedia 676 \n", "7 control Italian Wikipedia 5 \n", "8 test Italian Wikipedia 2820 \n", "9 control Japanese Wikipedia 1401 \n", "10 test Japanese Wikipedia 284 \n", "11 control Persian Wikipedia 1 \n", "12 test Persian Wikipedia 18 \n", "13 control Portuguese Wikipedia 4 \n", "14 test Portuguese Wikipedia 993 \n", "15 control Spanish Wikipedia 199 \n", "16 test Spanish Wikipedia 9 \n", "17 control Vietnamese Wikipedia 62 \n", "18 test Vietnamese Wikipedia 1 \n", " mean_response_time_minutes\n", "1 5003 \n", "2 6378 \n", "3 1023 \n", "4 3167 \n", "5 3159 \n", "6 1600 \n", "7 12 \n", "8 1549 \n", "9 4668 \n", "10 1534 \n", "11 2 \n", "12 643 \n", "13 4 \n", "14 797 \n", "15 2689 \n", "16 9 \n", "17 62 \n", "18 23 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# find the average time difference by wiki\n", "\n", "avg_time_response_bywiki <- topic_response_data_exp %>%\n", " filter(! wiki %in% c('AmharicWikipedia', 'Egyptian Wikipedia', \n", " 'Oromo Wikipedia', 'Hindi Wikipedia', 'Thai Wikipedia' , 'Bengali Wikipedia', \n", " 'Dutch Wikipedia', 'Polish Wikipedia', 'Ukrainian Wikipedia', \n", " 'Korean Wikipedia')) %>% # exclude wikis where there is not sufficient info\n", " mutate(response_time = difftime(response_dt, comment_dt, units = \"mins\")) %>% ## add column to show response time\n", " group_by(experiment_group, wiki) %>%\n", " summarise(median_response_time_minutes = as.integer(median(response_time)),\n", " mean_response_time_minutes = as.integer(mean(response_time))) %>%\n", " arrange(wiki)\n", "\n", "avg_time_response_bywiki" ] }, { "cell_type": "code", "execution_count": 46, "id": "8cc67959-a022-430c-afa7-a6e972ddff8b", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAACWAAAASwCAIAAADwxubWAAAACXBIWXMAABJ0AAASdAHeZh94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\nNBk5syRsWLYAAAAASUVORK5CYII=", "text/plain": [ "plot without title" ] }, "metadata": { "image/png": { "height": 600, "width": 1200 } }, "output_type": "display_data" } ], "source": [ "# Plot edit completion rates for each user on each wiki \n", "\n", "p <- avg_time_response_bywiki %>%\n", " ggplot(aes(x= experiment_group, y = median_response_time_minutes, fill = experiment_group)) +\n", " geom_col(position = 'dodge') +\n", " geom_text(aes(label = paste(median_response_time_minutes), fontface=2), vjust=1.2, size = 8, color = \"white\") +\n", " facet_wrap(~ wiki, scales = \"free_y\") +\n", " scale_y_continuous() +\n", " labs (y = \"Median response time in minutes\",\n", " title = \"Median response time by participating Wikipedia\",\n", " caption = \"Participating where we did not obtain a sufficent sample size of events were removed from this analysis\"\n", " )+\n", " scale_fill_manual(values= c(\"#999999\", \"steelblue2\"), name = \"Experiment Group\", labels = c(\"Control\", \"Test\")) +\n", " theme(\n", " panel.grid.minor = element_blank(),\n", " panel.background = element_blank(),\n", " plot.title = element_text(hjust = 0.5),\n", " text = element_text(size=16),\n", " legend.position=\"bottom\",\n", " axis.text.x = element_blank(),\n", " axis.title.x=element_blank(),\n", " axis.line = element_line(colour = \"black\")) \n", "\n", "p \n", "ggsave(\"Figures/avg_time_response_bywiki.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)" ] }, { "cell_type": "markdown", "id": "aab887bf-dc5c-465d-a8ea-dbfdda0ae08e", "metadata": {}, "source": [ "Results vary also on a per wikipedia basis with half of the participating wikis having signficant decrease in median response times and the other half having signficant increases. \n", "\n", "We observed signficant decreases in median response times for the following participating wikis: Spanish Wikipedia (-95% decrease), Japanese Wikipedia (-78% decrease), Vietnamese Wikipedia (-98% decrease), French Wikipedia (-16% decrease).\n", "\n", "We observed signficant increases in median response times for the following participating wikis: Portuguese Wikipedia, Persian Wikipedia, Italian Wikipedia and Hebrew Wikipedia). Furhter investigation is needed to clarfiy these results. " ] }, { "cell_type": "markdown", "id": "4f42be94-bce4-4356-aac2-f7026a28f26d", "metadata": {}, "source": [ "# Curiosities" ] }, { "cell_type": "markdown", "id": "89a9c196-9226-4646-8af1-e2a53077fd97", "metadata": {}, "source": [ "## Total number of comments posted by users within each experiment group\n", "### Overall" ] }, { "cell_type": "code", "execution_count": 33, "id": "7a3c8024-b59a-431e-b28d-4f9e9eb02c0e", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\n", "
A tibble: 2 × 3
experiment_groupn_usersn_comments
<chr><int><int>
control396421289
test 407620821
\n" ], "text/latex": [ "A tibble: 2 × 3\n", "\\begin{tabular}{lll}\n", " experiment\\_group & n\\_users & n\\_comments\\\\\n", " & & \\\\\n", "\\hline\n", "\t control & 3964 & 21289\\\\\n", "\t test & 4076 & 20821\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 2 × 3\n", "\n", "| experiment_group <chr> | n_users <int> | n_comments <int> |\n", "|---|---|---|\n", "| control | 3964 | 21289 |\n", "| test | 4076 | 20821 |\n", "\n" ], "text/plain": [ " experiment_group n_users n_comments\n", "1 control 3964 21289 \n", "2 test 4076 20821 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "talk_page_comments_overall <- topic_events %>%\n", " filter(edit_save_status == 'comment_posted',\n", " comment_type != 'topic' ) %>%\n", " group_by(experiment_group) %>%\n", " summarise(n_users = n_distinct(user_id),\n", " n_comments = n_distinct(edit_attempt_id), .groups = 'drop')\n", "\n", "talk_page_comments_overall" ] }, { "cell_type": "markdown", "id": "2f041291-da07-473f-9427-49a7ce4c5554", "metadata": {}, "source": [ "### By experience group" ] }, { "cell_type": "code", "execution_count": 34, "id": "f100f059-7bc3-4f5d-a87c-fa9d5600c286", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 6 × 4
experiment_groupexperience_groupn_usersn_comments
<chr><fct><int><int>
control0-100 edits 1783 3870
control101-500 edits 497 1790
controlover 500 edits177215629
test 0-100 edits 1852 4111
test 101-500 edits 539 1911
test over 500 edits177714799
\n" ], "text/latex": [ "A tibble: 6 × 4\n", "\\begin{tabular}{llll}\n", " experiment\\_group & experience\\_group & n\\_users & n\\_comments\\\\\n", " & & & \\\\\n", "\\hline\n", "\t control & 0-100 edits & 1783 & 3870\\\\\n", "\t control & 101-500 edits & 497 & 1790\\\\\n", "\t control & over 500 edits & 1772 & 15629\\\\\n", "\t test & 0-100 edits & 1852 & 4111\\\\\n", "\t test & 101-500 edits & 539 & 1911\\\\\n", "\t test & over 500 edits & 1777 & 14799\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 6 × 4\n", "\n", "| experiment_group <chr> | experience_group <fct> | n_users <int> | n_comments <int> |\n", "|---|---|---|---|\n", "| control | 0-100 edits | 1783 | 3870 |\n", "| control | 101-500 edits | 497 | 1790 |\n", "| control | over 500 edits | 1772 | 15629 |\n", "| test | 0-100 edits | 1852 | 4111 |\n", "| test | 101-500 edits | 539 | 1911 |\n", "| test | over 500 edits | 1777 | 14799 |\n", "\n" ], "text/plain": [ " experiment_group experience_group n_users n_comments\n", "1 control 0-100 edits 1783 3870 \n", "2 control 101-500 edits 497 1790 \n", "3 control over 500 edits 1772 15629 \n", "4 test 0-100 edits 1852 4111 \n", "5 test 101-500 edits 539 1911 \n", "6 test over 500 edits 1777 14799 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "talk_page_comments_bygroup <- topic_events %>%\n", " filter(edit_save_status == 'comment_posted',\n", " comment_type != 'topic' ) %>%\n", " group_by(experiment_group, experience_group) %>%\n", " summarise(n_users = n_distinct(user_id),\n", " n_comments = n_distinct(edit_attempt_id), .groups = 'drop')\n", "\n", "talk_page_comments_bygroup" ] }, { "cell_type": "markdown", "id": "50008398-29e7-48c2-a819-79024b25e71b", "metadata": {}, "source": [ "### Overall by comment type" ] }, { "cell_type": "code", "execution_count": 35, "id": "e3370c38-549e-4873-b3c1-7c3542f779d4", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 6 × 4
experiment_groupcomment_typen_usersn_comments
<chr><chr><int><int>
controlcomment 459 990
controlresponse382720388
controltopic 423616174
test comment 480 1056
test response394119881
test topic 429016511
\n" ], "text/latex": [ "A tibble: 6 × 4\n", "\\begin{tabular}{llll}\n", " experiment\\_group & comment\\_type & n\\_users & n\\_comments\\\\\n", " & & & \\\\\n", "\\hline\n", "\t control & comment & 459 & 990\\\\\n", "\t control & response & 3827 & 20388\\\\\n", "\t control & topic & 4236 & 16174\\\\\n", "\t test & comment & 480 & 1056\\\\\n", "\t test & response & 3941 & 19881\\\\\n", "\t test & topic & 4290 & 16511\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 6 × 4\n", "\n", "| experiment_group <chr> | comment_type <chr> | n_users <int> | n_comments <int> |\n", "|---|---|---|---|\n", "| control | comment | 459 | 990 |\n", "| control | response | 3827 | 20388 |\n", "| control | topic | 4236 | 16174 |\n", "| test | comment | 480 | 1056 |\n", "| test | response | 3941 | 19881 |\n", "| test | topic | 4290 | 16511 |\n", "\n" ], "text/plain": [ " experiment_group comment_type n_users n_comments\n", "1 control comment 459 990 \n", "2 control response 3827 20388 \n", "3 control topic 4236 16174 \n", "4 test comment 480 1056 \n", "5 test response 3941 19881 \n", "6 test topic 4290 16511 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "talk_page_comments_bytype <- topic_events %>%\n", " filter(edit_save_status == 'comment_posted') %>%\n", " group_by(experiment_group, comment_type) %>%\n", " summarise(n_users = n_distinct(user_id),\n", " n_comments = n_distinct(edit_attempt_id), .groups = 'drop')\n", "\n", "talk_page_comments_bytype" ] }, { "cell_type": "markdown", "id": "2117842a-3774-4a7b-9788-d1dbe86475e1", "metadata": {}, "source": [ "While there were no large changes in the number of comments posted by users in the test and control groups either by experience level or by comment type; however, we did observe some small differences:\n", "\n", "We observed a 6% increase in the number of comments posted by Junior Contributors (users with under 100 edits) and 7% increase in the number of comments posted by users with between 100 and 500 edits, while there was a 5% decrease in the number of comments posted Senior Contributors in the test group.\n" ] }, { "cell_type": "markdown", "id": "08af2e97-a41d-4e82-be4f-962275b7be22", "metadata": {}, "source": [ "## Percent of comments with a response\n", "\n", "We also reviewed the percent of all comments posted during the AB test that have received a response to date. For this analysis, we identified comments with a response by looking for any comment id that were also once a comment_parent_id (indicating a response to a new comment) or any comment_parent_id that were also once a topic_id (indicating a response to topic). \n" ] }, { "cell_type": "markdown", "id": "7b90f456-d846-49e0-98c1-94e13808a103", "metadata": {}, "source": [ "### Overall" ] }, { "cell_type": "code", "execution_count": 36, "id": "b945d0b3-e9d4-4902-987f-350ecc62eb22", "metadata": {}, "outputs": [], "source": [ "# Find all all topics or new comments that have received a response. \n", "# Topics with response - commment parent id = topic_id\n", "# Comments with a response - comment_id = comment_parent id\n", "\n", "comments_w_response_overall <- topic_events %>%\n", " filter(comment_type != 'topic') %>% #all topics by definition have a comment added to them\n", " filter(edit_save_status == 'comment_posted',\n", " comment_id %in% comment_parent_id |\n", " comment_parent_id %in% topic_id ) %>% # comments and topics that recieved a response\n", " group_by(experiment_group) %>%\n", " summarise(n_users_wresponse = n_distinct(user_id),\n", " n_comments_wresponse = n_distinct(edit_attempt_id), .groups = 'drop')\n" ] }, { "cell_type": "code", "execution_count": 37, "id": "40380dce-4155-49bd-b86a-89a3d2cf3146", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\n", "
A grouped_df: 2 × 7
experiment_groupn_usersn_commentsn_users_wresponsen_comments_wresponsepct_users_w_reponsepct_comments_w_reponse
<chr><int><int><int><int><chr><chr>
control3964212891552646139.15%30.35%
test 4076208211574634338.62%30.46%
\n" ], "text/latex": [ "A grouped\\_df: 2 × 7\n", "\\begin{tabular}{lllllll}\n", " experiment\\_group & n\\_users & n\\_comments & n\\_users\\_wresponse & n\\_comments\\_wresponse & pct\\_users\\_w\\_reponse & pct\\_comments\\_w\\_reponse\\\\\n", " & & & & & & \\\\\n", "\\hline\n", "\t control & 3964 & 21289 & 1552 & 6461 & 39.15\\% & 30.35\\%\\\\\n", "\t test & 4076 & 20821 & 1574 & 6343 & 38.62\\% & 30.46\\%\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A grouped_df: 2 × 7\n", "\n", "| experiment_group <chr> | n_users <int> | n_comments <int> | n_users_wresponse <int> | n_comments_wresponse <int> | pct_users_w_reponse <chr> | pct_comments_w_reponse <chr> |\n", "|---|---|---|---|---|---|---|\n", "| control | 3964 | 21289 | 1552 | 6461 | 39.15% | 30.35% |\n", "| test | 4076 | 20821 | 1574 | 6343 | 38.62% | 30.46% |\n", "\n" ], "text/plain": [ " experiment_group n_users n_comments n_users_wresponse n_comments_wresponse\n", "1 control 3964 21289 1552 6461 \n", "2 test 4076 20821 1574 6343 \n", " pct_users_w_reponse pct_comments_w_reponse\n", "1 39.15% 30.35% \n", "2 38.62% 30.46% " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# find percent reponse rate\n", "response_pct_overall <- inner_join(talk_page_comments_overall, comments_w_response_overall, by = c(\"experiment_group\")) %>%\n", " group_by(experiment_group) %>%\n", " mutate(pct_users_w_reponse = paste0(round(n_users_wresponse/n_users * 100, 2), \"%\"),\n", " pct_comments_w_reponse = paste0(round(n_comments_wresponse/n_comments * 100, 2), \"%\"))\n", "response_pct_overall" ] }, { "cell_type": "markdown", "id": "b0afa198-c17f-49f6-8b00-9b82fc3c5bc2", "metadata": {}, "source": [ "There was a very slight (0.36%) increase in the percent of comments with a response in the test group." ] }, { "cell_type": "markdown", "id": "79b9cd72-9e4e-4046-97b2-dc42a1a83730", "metadata": {}, "source": [ "### By Experience Group" ] }, { "cell_type": "code", "execution_count": 38, "id": "06320d52-4c9f-4b98-8ac0-73b559d69057", "metadata": {}, "outputs": [], "source": [ "# Find all all topics or new comments that have received a response. \n", "# Topics with response - commment parent id = topic_id\n", "# Comments with a response - comment_id = comment_parent id\n", "\n", "comments_w_response_bygroup <- topic_events %>%\n", " filter(comment_type != 'topic') %>% #all topics by definition have a comment added to them\n", " filter(edit_save_status == 'comment_posted',\n", " comment_id %in% comment_parent_id |\n", " comment_parent_id %in% topic_id ) %>% # comments and topics that recieved a response\n", " group_by(experiment_group, experience_group) %>%\n", " summarise(n_users_wresponse = n_distinct(user_id),\n", " n_comments_wresponse = n_distinct(edit_attempt_id), .groups = 'drop')\n" ] }, { "cell_type": "code", "execution_count": 39, "id": "9668a65d-119f-4473-aec2-bd1c7a34ff0a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A grouped_df: 6 × 8
experiment_groupexperience_groupn_usersn_commentsn_users_wresponsen_comments_wresponsepct_users_w_reponsepct_comments_w_reponse
<chr><fct><int><int><int><int><chr><chr>
control0-100 edits 1783 3870512 89228.72%23.05%
control101-500 edits 497 1790185 45537.22%25.42%
controlover 500 edits177215629886511450% 32.72%
test 0-100 edits 1852 4111534102928.83%25.03%
test 101-500 edits 539 1911181 56033.58%29.3%
test over 500 edits177714799890475450.08%32.12%
\n" ], "text/latex": [ "A grouped\\_df: 6 × 8\n", "\\begin{tabular}{llllllll}\n", " experiment\\_group & experience\\_group & n\\_users & n\\_comments & n\\_users\\_wresponse & n\\_comments\\_wresponse & pct\\_users\\_w\\_reponse & pct\\_comments\\_w\\_reponse\\\\\n", " & & & & & & & \\\\\n", "\\hline\n", "\t control & 0-100 edits & 1783 & 3870 & 512 & 892 & 28.72\\% & 23.05\\%\\\\\n", "\t control & 101-500 edits & 497 & 1790 & 185 & 455 & 37.22\\% & 25.42\\%\\\\\n", "\t control & over 500 edits & 1772 & 15629 & 886 & 5114 & 50\\% & 32.72\\%\\\\\n", "\t test & 0-100 edits & 1852 & 4111 & 534 & 1029 & 28.83\\% & 25.03\\%\\\\\n", "\t test & 101-500 edits & 539 & 1911 & 181 & 560 & 33.58\\% & 29.3\\% \\\\\n", "\t test & over 500 edits & 1777 & 14799 & 890 & 4754 & 50.08\\% & 32.12\\%\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A grouped_df: 6 × 8\n", "\n", "| experiment_group <chr> | experience_group <fct> | n_users <int> | n_comments <int> | n_users_wresponse <int> | n_comments_wresponse <int> | pct_users_w_reponse <chr> | pct_comments_w_reponse <chr> |\n", "|---|---|---|---|---|---|---|---|\n", "| control | 0-100 edits | 1783 | 3870 | 512 | 892 | 28.72% | 23.05% |\n", "| control | 101-500 edits | 497 | 1790 | 185 | 455 | 37.22% | 25.42% |\n", "| control | over 500 edits | 1772 | 15629 | 886 | 5114 | 50% | 32.72% |\n", "| test | 0-100 edits | 1852 | 4111 | 534 | 1029 | 28.83% | 25.03% |\n", "| test | 101-500 edits | 539 | 1911 | 181 | 560 | 33.58% | 29.3% |\n", "| test | over 500 edits | 1777 | 14799 | 890 | 4754 | 50.08% | 32.12% |\n", "\n" ], "text/plain": [ " experiment_group experience_group n_users n_comments n_users_wresponse\n", "1 control 0-100 edits 1783 3870 512 \n", "2 control 101-500 edits 497 1790 185 \n", "3 control over 500 edits 1772 15629 886 \n", "4 test 0-100 edits 1852 4111 534 \n", "5 test 101-500 edits 539 1911 181 \n", "6 test over 500 edits 1777 14799 890 \n", " n_comments_wresponse pct_users_w_reponse pct_comments_w_reponse\n", "1 892 28.72% 23.05% \n", "2 455 37.22% 25.42% \n", "3 5114 50% 32.72% \n", "4 1029 28.83% 25.03% \n", "5 560 33.58% 29.3% \n", "6 4754 50.08% 32.12% " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# find percent reponse rate\n", "response_pct_bygroup <- inner_join(talk_page_comments_bygroup, comments_w_response_bygroup, by = c(\"experiment_group\", \"experience_group\")) %>%\n", " group_by(experiment_group) %>%\n", " mutate(pct_users_w_reponse = paste0(round(n_users_wresponse/n_users * 100, 2), \"%\"),\n", " pct_comments_w_reponse = paste0(round(n_comments_wresponse/n_comments * 100, 2), \"%\"))\n", "response_pct_bygroup" ] }, { "cell_type": "code", "execution_count": 40, "id": "f1ad7ab3-a63d-4265-8ece-d6a47ca83b8c", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Comment response rate across all participating Wikipedias By experience level
Experience GroupPercent of comments with a response1
control
0-100 edits23.05%
101-500 edits25.42%
over 500 edits32.72%
test
0-100 edits25.03%
101-500 edits29.3%
over 500 edits32.12%
\n", "

\n", " \n", " 1\n", " \n", " \n", " Of all the comments posted by users in the AB test, the percent of comments that recevied a response by the end of the AB test\n", "
\n", "

\n", "
\n", "\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "NULL" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Create table of completion rate\n", "response_pct_table <- response_pct_bygroup %>%\n", " select(c(1,2,8))%>% # select relevant rows\n", " gt() %>%\n", " tab_header(\n", " title = \"Comment response rate across all participating Wikipedias By experience level\",\n", " ) %>%\n", " cols_label(\n", " experiment_group = \"Experiment Group\",\n", " experience_group = \"Experience Group\",\n", " pct_comments_w_reponse = \"Percent of comments with a response\"\n", " ) %>%\n", " tab_footnote(\n", " footnote = \"Of all the comments posted by users in the AB test, the percent of comments that recevied a response by the end of the AB test\",\n", " locations = cells_column_labels(\n", " columns = \"pct_comments_w_reponse\"\n", " )) %>%\n", " gtsave(\n", " \"response_pct_table.html\", inline_css = TRUE)\n", "\n", "IRdisplay::display_html(data = response_pct_table, file = \"response_pct_table.html\")\n", "\n", "response_pct_table" ] }, { "cell_type": "code", "execution_count": 121, "id": "b4991daa-ee70-4465-926b-425885e3b322", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAACWAAAASwCAIAAADwxubWAAAACXBIWXMAABJ0AAASdAHeZh94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\n", "text/plain": [ "plot without title" ] }, "metadata": { "image/png": { "height": 600, "width": 1200 } }, "output_type": "display_data" } ], "source": [ "# Plot response_pct\n", "\n", "p <- response_pct_bygroup %>%\n", " ggplot(aes(x= experiment_group, y = n_comments_wresponse/n_comments, fill = experiment_group)) +\n", " geom_col(position = 'dodge') +\n", " geom_text(aes(label = paste0(round(n_comments_wresponse/n_comments * 100, 2), \"%\"), fontface=2), vjust=1.2, size = 8, color = \"white\") +\n", " facet_wrap(~ experience_group, scales = \"free_y\") +\n", " scale_y_continuous(label = scales::percent ) +\n", " labs (y = \"Percent of comments with a response\",\n", " title = \"Percent of comments with a response in the AB test by experience level\"\n", " )+\n", " scale_fill_manual(values= c(\"#999999\", \"steelblue2\"), name = \"Experiment Group\", labels = c(\"Control (Topic subscriptions disabled)\", \"Test (Topic subscriptions enabled)\")) +\n", " theme(\n", " panel.grid.minor = element_blank(),\n", " panel.background = element_blank(),\n", " plot.title = element_text(hjust = 0.5),\n", " text = element_text(size=22),\n", " legend.position=\"bottom\",\n", " axis.text.x = element_blank(),\n", " axis.title.x=element_blank(),\n", " axis.line = element_line(colour = \"black\")) \n", "\n", "p \n", "ggsave(\"Figures/overall_response_pct.png\", p, width = 20, height = 11, units = \"in\", dpi = 300)\n", "\n" ] }, { "cell_type": "markdown", "id": "88f02590-b799-4670-8ae1-2c75d090eadc", "metadata": {}, "source": [ "When broken down by the user's experience level, we see some slightly larger differences between the two experiment groups.\n", "* There was a 8.6% increase in the percent of comments posted by Junior contributors (under 100 edits) with a response.\n", "* There was 15.3% increase in the percent of comments posted by Contributors with 100-500 edits with a response.\n", "* In contrast, there was -1.8% decrease in the percent of comments posted by Contributors with over 500 edits. " ] }, { "cell_type": "markdown", "id": "03cd3f50-7726-45fe-9c8c-53a501bad97a", "metadata": {}, "source": [ "### Average and total number of comments or new topics posted on talk pages by contributors that edit a talk page, grouped by experience level" ] }, { "cell_type": "markdown", "id": "7d3183b5-689c-460f-9155-fec703ce8f87", "metadata": {}, "source": [ "### Average daily number of comments or new topics across all contributors" ] }, { "cell_type": "code", "execution_count": 470, "id": "336d2fb2-d874-42e7-9605-8688e4c6269f", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'save_dt' (override with `.groups` argument)\n", "\n", "`summarise()` ungrouping output (override with `.groups` argument)\n", "\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\n", "
A tibble: 2 × 2
experiment_groupn_comments_total
<chr><dbl>
control668.3864
test 655.0000
\n" ], "text/latex": [ "A tibble: 2 × 2\n", "\\begin{tabular}{ll}\n", " experiment\\_group & n\\_comments\\_total\\\\\n", " & \\\\\n", "\\hline\n", "\t control & 668.3864\\\\\n", "\t test & 655.0000\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 2 × 2\n", "\n", "| experiment_group <chr> | n_comments_total <dbl> |\n", "|---|---|\n", "| control | 668.3864 |\n", "| test | 655.0000 |\n", "\n" ], "text/plain": [ " experiment_group n_comments_total\n", "1 control 668.3864 \n", "2 test 655.0000 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "avg_daily_comments <- topic_events %>%\n", " filter(edit_save_status == 'comment_posted') %>%\n", " group_by(save_dt, experiment_group) %>%\n", " summarise(n_comments_total = n_distinct(comment_id)) %>%\n", " group_by(experiment_group) %>%\n", "summarise(n_comments_total = mean(n_comments_total))\n", "\n", "avg_daily_comments" ] }, { "cell_type": "markdown", "id": "2933aaef-9365-458a-8f92-444be0771b68", "metadata": {}, "source": [ "### Average daily number of comments or new topic by contributors' experience level" ] }, { "cell_type": "code", "execution_count": 468, "id": "20254bb8-28de-4a23-9276-eb4e3ee3fe3c", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'user_id', 'experiment_group' (override with `.groups` argument)\n", "\n", "`summarise()` regrouping output by 'experiment_group' (override with `.groups` argument)\n", "\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A grouped_df: 6 × 3
experiment_groupexperience_groupavg_comments
<chr><fct><dbl>
control0-100 edits 2.04
control101-500 edits 3.80
controlover 500 edits10.53
test 0-100 edits 2.12
test 101-500 edits 3.78
test over 500 edits10.12
\n" ], "text/latex": [ "A grouped\\_df: 6 × 3\n", "\\begin{tabular}{lll}\n", " experiment\\_group & experience\\_group & avg\\_comments\\\\\n", " & & \\\\\n", "\\hline\n", "\t control & 0-100 edits & 2.04\\\\\n", "\t control & 101-500 edits & 3.80\\\\\n", "\t control & over 500 edits & 10.53\\\\\n", "\t test & 0-100 edits & 2.12\\\\\n", "\t test & 101-500 edits & 3.78\\\\\n", "\t test & over 500 edits & 10.12\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A grouped_df: 6 × 3\n", "\n", "| experiment_group <chr> | experience_group <fct> | avg_comments <dbl> |\n", "|---|---|---|\n", "| control | 0-100 edits | 2.04 |\n", "| control | 101-500 edits | 3.80 |\n", "| control | over 500 edits | 10.53 |\n", "| test | 0-100 edits | 2.12 |\n", "| test | 101-500 edits | 3.78 |\n", "| test | over 500 edits | 10.12 |\n", "\n" ], "text/plain": [ " experiment_group experience_group avg_comments\n", "1 control 0-100 edits 2.04 \n", "2 control 101-500 edits 3.80 \n", "3 control over 500 edits 10.53 \n", "4 test 0-100 edits 2.12 \n", "5 test 101-500 edits 3.78 \n", "6 test over 500 edits 10.12 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "## Average number of comments or new topics by each distinct contributor grouped by experience level\n", "\n", "avg_daily_comments_bycontributor <- topic_events %>%\n", " filter(edit_save_status == 'comment_posted') %>%\n", " group_by(user_id, experiment_group, experience_group) %>%\n", " summarise(n_comments_total = n_distinct(comment_id)) %>%\n", " group_by(experiment_group, experience_group) %>%\n", "summarise(avg_comments = round(mean(n_comments_total), 2))\n", "\n", "avg_daily_comments_bycontributor" ] }, { "cell_type": "markdown", "id": "839ce362-0777-4bc3-a322-e2d7def6377f", "metadata": {}, "source": [ "There is also no signficant differences in the average number of comments posted by a distinct logged-in contributor in the AB test. In both groups, the number of average comments increase with as te contributors' edit experience increase." ] }, { "cell_type": "markdown", "id": "c0f3428b-b1ae-41d1-932c-f3531626740a", "metadata": {}, "source": [ "# Curiosity 2: Percent of contributors that edit a talk page and start a new topic, grouped by the number of topics (e.g. 1-5, 6-10, 11-15, etc) they've started and experience level\n" ] }, { "cell_type": "markdown", "id": "66362938-db67-4917-9124-d00987a9bb77", "metadata": {}, "source": [ "## What percent of contributors edit a talk page and start a new topic?\n", "### Overall" ] }, { "cell_type": "code", "execution_count": 81, "id": "bb7d15e8-6393-4455-8660-9219b6fdcfd8", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` ungrouping output (override with `.groups` argument)\n", "\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\n", "
A tibble: 2 × 6
experiment_groupn_topic_postersn_comment_postersn_talk_editorspct_topic_posterspct_commenter_posters
<chr><int><int><int><chr><chr>
control3295357850838.728%4.196%
test 3296362847938.873%4.269%
\n" ], "text/latex": [ "A tibble: 2 × 6\n", "\\begin{tabular}{llllll}\n", " experiment\\_group & n\\_topic\\_posters & n\\_comment\\_posters & n\\_talk\\_editors & pct\\_topic\\_posters & pct\\_commenter\\_posters\\\\\n", " & & & & & \\\\\n", "\\hline\n", "\t control & 3295 & 357 & 8508 & 38.728\\% & 4.196\\%\\\\\n", "\t test & 3296 & 362 & 8479 & 38.873\\% & 4.269\\%\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 2 × 6\n", "\n", "| experiment_group <chr> | n_topic_posters <int> | n_comment_posters <int> | n_talk_editors <int> | pct_topic_posters <chr> | pct_commenter_posters <chr> |\n", "|---|---|---|---|---|---|\n", "| control | 3295 | 357 | 8508 | 38.728% | 4.196% |\n", "| test | 3296 | 362 | 8479 | 38.873% | 4.269% |\n", "\n" ], "text/plain": [ " experiment_group n_topic_posters n_comment_posters n_talk_editors\n", "1 control 3295 357 8508 \n", "2 test 3296 362 8479 \n", " pct_topic_posters pct_commenter_posters\n", "1 38.728% 4.196% \n", "2 38.873% 4.269% " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pct_editors_comments <- topic_events %>%\n", " group_by(experiment_group) %>%\n", " summarise(n_topic_posters = n_distinct(user_id[edit_save_status == 'comment_posted' &\n", " comment_type == 'topic']),\n", " n_comment_posters = n_distinct(user_id[edit_save_status == 'comment_posted' &\n", " comment_type == 'comment']),\n", " n_talk_editors = n_distinct(user_id),\n", " pct_topic_posters = paste0(round(n_topic_posters/n_talk_editors * 100, 3), \"%\"),\n", " pct_commenter_posters = paste0(round(n_comment_posters/n_talk_editors * 100, 3), \"%\"))\n", "\n", "pct_editors_comments" ] }, { "cell_type": "markdown", "id": "de41b1dd-adf4-4cf0-96e3-12e606368232", "metadata": {}, "source": [ "### By experience group" ] }, { "cell_type": "code", "execution_count": 96, "id": "ef4f3930-3fa4-4be8-a7c8-b088cf0dff72", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'experiment_group' (override with `.groups` argument)\n", "\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A grouped_df: 6 × 7
experiment_groupexperience_groupn_topic_postersn_comment_postersn_talk_editorspct_topic_posterspct_commenter_posters
<chr><fct><int><int><int><chr><chr>
control0-100 edits 1455 63503828.881%1.25%
control101-500 edits 362 29 80145.194%3.62%
controlover 500 edits1525265278854.699%9.505%
test 0-100 edits 1444 55504028.651%1.091%
test 101-500 edits 390 28 83346.819%3.361%
test over 500 edits1519281273755.499%10.267%
\n" ], "text/latex": [ "A grouped\\_df: 6 × 7\n", "\\begin{tabular}{lllllll}\n", " experiment\\_group & experience\\_group & n\\_topic\\_posters & n\\_comment\\_posters & n\\_talk\\_editors & pct\\_topic\\_posters & pct\\_commenter\\_posters\\\\\n", " & & & & & & \\\\\n", "\\hline\n", "\t control & 0-100 edits & 1455 & 63 & 5038 & 28.881\\% & 1.25\\% \\\\\n", "\t control & 101-500 edits & 362 & 29 & 801 & 45.194\\% & 3.62\\% \\\\\n", "\t control & over 500 edits & 1525 & 265 & 2788 & 54.699\\% & 9.505\\% \\\\\n", "\t test & 0-100 edits & 1444 & 55 & 5040 & 28.651\\% & 1.091\\% \\\\\n", "\t test & 101-500 edits & 390 & 28 & 833 & 46.819\\% & 3.361\\% \\\\\n", "\t test & over 500 edits & 1519 & 281 & 2737 & 55.499\\% & 10.267\\%\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A grouped_df: 6 × 7\n", "\n", "| experiment_group <chr> | experience_group <fct> | n_topic_posters <int> | n_comment_posters <int> | n_talk_editors <int> | pct_topic_posters <chr> | pct_commenter_posters <chr> |\n", "|---|---|---|---|---|---|---|\n", "| control | 0-100 edits | 1455 | 63 | 5038 | 28.881% | 1.25% |\n", "| control | 101-500 edits | 362 | 29 | 801 | 45.194% | 3.62% |\n", "| control | over 500 edits | 1525 | 265 | 2788 | 54.699% | 9.505% |\n", "| test | 0-100 edits | 1444 | 55 | 5040 | 28.651% | 1.091% |\n", "| test | 101-500 edits | 390 | 28 | 833 | 46.819% | 3.361% |\n", "| test | over 500 edits | 1519 | 281 | 2737 | 55.499% | 10.267% |\n", "\n" ], "text/plain": [ " experiment_group experience_group n_topic_posters n_comment_posters\n", "1 control 0-100 edits 1455 63 \n", "2 control 101-500 edits 362 29 \n", "3 control over 500 edits 1525 265 \n", "4 test 0-100 edits 1444 55 \n", "5 test 101-500 edits 390 28 \n", "6 test over 500 edits 1519 281 \n", " n_talk_editors pct_topic_posters pct_commenter_posters\n", "1 5038 28.881% 1.25% \n", "2 801 45.194% 3.62% \n", "3 2788 54.699% 9.505% \n", "4 5040 28.651% 1.091% \n", "5 833 46.819% 3.361% \n", "6 2737 55.499% 10.267% " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pct_editors_comments_exp <- topic_events %>%\n", " group_by(experiment_group, experience_group) %>%\n", " summarise(n_topic_posters = n_distinct(user_id[edit_save_status == 'comment_posted' &\n", " comment_type == 'topic']),\n", " n_comment_posters = n_distinct(user_id[edit_save_status == 'comment_posted' &\n", " comment_type == 'comment']),\n", " n_talk_editors = n_distinct(user_id),\n", " pct_topic_posters = paste0(round(n_topic_posters/n_talk_editors * 100, 3), \"%\"),\n", " pct_commenter_posters = paste0(round(n_comment_posters/n_talk_editors * 100, 3), \"%\"))\n", "\n", "pct_editors_comments_exp" ] }, { "cell_type": "markdown", "id": "b4254484-8f7d-492f-afe5-e9a9c99ab980", "metadata": {}, "source": [ "We did not observe any significant differences in the overall percent of contributors that edit a talk page and start a new topic. Of the talk page contributors that made an edit, a slightly higher percentage of test group contributors started a new topic **( 38.7% → 38.8%; 0.4% ↑)**.\n", "\n", "We observed only slight differences in percentages across each experience level. A slightly higher percentage (+1.7%) of all Senior Contributors that made a talk page edit in the test group started a new topic while a slightly lower percenrage of Junior contributors in the test group started a new topic (-1.11%)\n", "\n", "Note: This includes all contributors that made an edit to a talk page including corrective edits." ] }, { "cell_type": "markdown", "id": "950e45ec-9c20-4e8f-9e94-8b22e16e14a9", "metadata": {}, "source": [ "## Number of comments or topics posted on a talk page by contributors" ] }, { "cell_type": "code", "execution_count": 74, "id": "4c6aa0f7-ff70-44bb-bdd2-bf9fe3508aa3", "metadata": {}, "outputs": [], "source": [ "## Break into groups\n", "\n", "b <- c(0, 1, 2 ,3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, Inf)\n", "names <- c('1', '2', '3', '4', '5', '6', '7', '8',\n", " '9', '10', '11', '12', '13', '14', '15', 'over 15')" ] }, { "cell_type": "markdown", "id": "ac550175-8a8f-41c4-8619-d6e4d8eefe88", "metadata": {}, "source": [ "### Overall across all participating wikis" ] }, { "cell_type": "code", "execution_count": 75, "id": "bb50253b-8e13-4107-b7bb-3bfa6c13acd0", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'experiment_group' (override with `.groups` argument)\n", "\n", "`summarise()` regrouping output by 'experiment_group' (override with `.groups` argument)\n", "\n" ] } ], "source": [ "topic_contributors_bygroup <- topic_events %>%\n", " #filter(comment_type == 'topic') %>%\n", " group_by(experiment_group, user_id) %>%\n", " summarise(n_comments = n_distinct(comment_id)) %>%\n", " mutate(topic_count_group = cut(n_comments, breaks = b, labels = names)) %>%\n", " group_by(experiment_group, topic_count_group)%>%\n", " summarise(n_users = n_distinct(user_id)) %>%\n", " mutate(percent_users = n_users/sum(n_users))\n" ] }, { "cell_type": "code", "execution_count": 89, "id": "764437fd-031c-458c-aefd-b3d8604a153a", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAACWAAAASwCAIAAADwxubWAAAACXBIWXMAABJ0AAASdAHeZh94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\nAAAAAABgQP4/WdtZl/0QO3QAAAAASUVORK5CYII=", "text/plain": [ "plot without title" ] }, "metadata": { "image/png": { "height": 600, "width": 1200 } }, "output_type": "display_data" } ], "source": [ "# Chart groups\n", "\n", "p <- topic_contributors_bygroup %>%\n", " ggplot(aes(x=topic_count_group, y = percent_users, fill =experiment_group)) +\n", " geom_col(position = 'dodge') +\n", " scale_y_continuous(labels = scales::percent) +\n", " labs (y = \"Percent of talk page contributors\",\n", " x = \"Number of comments posted on a talk page\",\n", " title = \"Percent of contributors that posted a comment on a talk page by number of topics\") +\n", " scale_fill_manual(values= c(\"#999999\", \"steelblue2\"), name = \"Experiment Group\", labels = c(\"Control\", \"Test\")) + \n", " theme(\n", " panel.grid.minor = element_blank(),\n", " panel.background = element_blank(),\n", " plot.title = element_text(hjust = 0.5),\n", " text = element_text(size=16),\n", " legend.position=\"bottom\",\n", " axis.line = element_line(colour = \"black\")) \n", "p\n", "\n", "ggsave(\"Figures/topic_contributors_bygroup.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)" ] }, { "cell_type": "markdown", "id": "3bfe5b04-2d61-43a8-a33f-cfa574b8d33e", "metadata": {}, "source": [ "There are no signficant differences in the number of comments posted on a talk pages by the bucketed users in the test and control groups. For both groups, the majority of contributors (60% in each experiment group) posted only one comment during the duration of the AB test. \n", "\n", "4% of contributors within each group were highly active (posting over 15 comments on a talk page during the duration of the AB test)" ] }, { "cell_type": "markdown", "id": "c17eb2eb-e3fc-4d01-886a-28d184464cd6", "metadata": {}, "source": [ "### By experience group" ] }, { "cell_type": "code", "execution_count": 81, "id": "7f2117dc-b395-4c7f-9f6a-06d19e7d59ac", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'experiment_group', 'experience_group' (override with `.groups` argument)\n", "\n", "`summarise()` regrouping output by 'experiment_group', 'experience_group' (override with `.groups` argument)\n", "\n" ] } ], "source": [ "topic_contributors_bygroupexp <- topic_events %>%\n", " #filter(comment_type == 'topic') %>%\n", " group_by(experiment_group,experience_group, user_id) %>%\n", " summarise(n_comments = n_distinct(comment_id)) %>%\n", " mutate(topic_count_group = cut(n_comments, breaks = b, labels = names)) %>%\n", " group_by(experiment_group, experience_group, topic_count_group)%>%\n", " summarise(n_users = n_distinct(user_id)) %>%\n", " mutate(percent_users = n_users/sum(n_users))\n" ] }, { "cell_type": "code", "execution_count": 88, "id": "0c139311-1aa3-44a4-bcc7-0a039d456827", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAACWAAAASwCAIAAADwxubWAAAACXBIWXMAABJ0AAASdAHeZh94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\ncCAEhAAAAAAAAAAAAIAD+Q/K1oH4Wt7tygAAAABJRU5ErkJggg==", "text/plain": [ "plot without title" ] }, "metadata": { "image/png": { "height": 600, "width": 1200 } }, "output_type": "display_data" } ], "source": [ "# Chart groups by exp\n", "\n", "p <- topic_contributors_bygroupexp %>%\n", " ggplot(aes(x=topic_count_group, y = percent_users, fill =experiment_group)) +\n", " geom_col(position = 'dodge') +\n", " facet_grid(~ experience_group) +\n", " scale_y_continuous(labels = scales::percent) +\n", " labs (y = \"Percent of talk page contributors\",\n", " x = \"Number of comments posted on a talk page\",\n", " title = \"Percent of contributors that posted a comment on a talk page by number of topics\") +\n", " scale_fill_manual(values= c(\"#999999\", \"steelblue2\"), name = \"Experiment Group\", labels = c(\"Control\", \"Test\")) + \n", " theme(\n", " panel.grid.minor = element_blank(),\n", " panel.background = element_blank(),\n", " plot.title = element_text(hjust = 0.5),\n", " text = element_text(size=16),\n", " legend.position=\"bottom\",\n", " axis.line = element_line(colour = \"black\")) \n", "p\n", "\n", "ggsave(\"Figures/topic_contributors_bygroup_exp.png\", p, width = 16, height = 8, units = \"in\", dpi = 300)" ] }, { "cell_type": "markdown", "id": "2762f9e9-348c-4ba8-9ba3-0e55b6b3b137", "metadata": {}, "source": [ "Broken down by experience level, both the test and control experiment groups follow similar trends. Junior contributors most frequently just posted one new topic during the AB test. Senior contributors in both experiment groups typically started a higher number of new topics during the AB test compared to Junior Contribtors." ] }, { "cell_type": "markdown", "id": "81392e59-9a45-4091-a81e-d394aaeb5b4d", "metadata": {}, "source": [ "# Guardrails" ] }, { "cell_type": "markdown", "id": "8acc89a0-c1e6-43f9-a667-8b450dbba325", "metadata": {}, "source": [ "# Guardrail #1: Topic Subscriptions should not cause a significant increase in disruptive behavior.\n", "\n", "We looked at the following two metrics as indicators of disruption:\n", "A) Sharp increase in the number of notifications sent/contributor/day and B) Sharp increase in the percent of contributors that disable notifications." ] }, { "cell_type": "markdown", "id": "76118203-951c-432d-8d23-e7769313da64", "metadata": {}, "source": [ "## A) Sharp increase in the number of notifications sent/contributor/day \n", "\n", "**Data Source**: [echo_notification table](https://www.mediawiki.org/wiki/Extension:Echo/echo_notification_table?useskin=vector-2022)\n", "\n", "Note: Results are limited to participating wikis but not only bucketed users. " ] }, { "cell_type": "code", "execution_count": 49, "id": "546b1729-434e-4b6b-b239-4afa0dbc8c76", "metadata": {}, "outputs": [], "source": [ "notifications_sent <-\n", " read.csv(\n", " file = 'Data/notifications_sent.csv',\n", " header = TRUE,\n", " sep = \",\",\n", " stringsAsFactors = FALSE\n", " ) # loads notification data" ] }, { "cell_type": "code", "execution_count": 50, "id": "89ed97a2-720e-4e9d-95c8-7b6e4effb4f4", "metadata": {}, "outputs": [], "source": [ "# remove scientific notations\n", "options(scipen=999)" ] }, { "cell_type": "code", "execution_count": 51, "id": "e61bcb28-01e9-4fa7-9bdd-d9cae890d0ca", "metadata": {}, "outputs": [], "source": [ "# convert time sent to date time\n", "notifications_sent$time_sent <- as.Date(as.character(notifications_sent$time_sent), format = \"%Y%m%d%H%M%S\")" ] }, { "cell_type": "code", "execution_count": 52, "id": "7e62c00a-7d68-4844-a2f4-c3c299ae0b78", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A data.frame: 6 × 3
notification_usertime_sentnum_notifications
<int><date><int>
1 366402021-08-271
2 366402022-01-271
3 366402022-04-291
41240782021-08-271
5 402021-11-301
6 442302022-03-311
\n" ], "text/latex": [ "A data.frame: 6 × 3\n", "\\begin{tabular}{r|lll}\n", " & notification\\_user & time\\_sent & num\\_notifications\\\\\n", " & & & \\\\\n", "\\hline\n", "\t1 & 36640 & 2021-08-27 & 1\\\\\n", "\t2 & 36640 & 2022-01-27 & 1\\\\\n", "\t3 & 36640 & 2022-04-29 & 1\\\\\n", "\t4 & 124078 & 2021-08-27 & 1\\\\\n", "\t5 & 40 & 2021-11-30 & 1\\\\\n", "\t6 & 44230 & 2022-03-31 & 1\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A data.frame: 6 × 3\n", "\n", "| | notification_user <int> | time_sent <date> | num_notifications <int> |\n", "|---|---|---|---|\n", "| 1 | 36640 | 2021-08-27 | 1 |\n", "| 2 | 36640 | 2022-01-27 | 1 |\n", "| 3 | 36640 | 2022-04-29 | 1 |\n", "| 4 | 124078 | 2021-08-27 | 1 |\n", "| 5 | 40 | 2021-11-30 | 1 |\n", "| 6 | 44230 | 2022-03-31 | 1 |\n", "\n" ], "text/plain": [ " notification_user time_sent num_notifications\n", "1 36640 2021-08-27 1 \n", "2 36640 2022-01-27 1 \n", "3 36640 2022-04-29 1 \n", "4 124078 2021-08-27 1 \n", "5 40 2021-11-30 1 \n", "6 44230 2022-03-31 1 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "head(notifications_sent)" ] }, { "cell_type": "code", "execution_count": 63, "id": "8cc5ea68-7889-4963-95d3-5e39d4ee1a66", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'notification_user' (override with `.groups` argument)\n", "\n", "`summarise()` ungrouping output (override with `.groups` argument)\n", "\n" ] } ], "source": [ "# calculate avg notifications sent per user per day\n", "notifications_sent_byday <- notifications_sent %>%\n", " group_by(notification_user, time_sent) %>%\n", " summarise(n_notifications = sum(num_notifications)) %>%\n", " group_by(time_sent) %>%\n", " summarise(avg_daily_notifications = mean(n_notifications))\n", " " ] }, { "cell_type": "code", "execution_count": 102, "id": "f2f2919f-66ce-4621-8baf-38cc8ee71df2", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAACWAAAASwCAIAAADwxubWAAAACXBIWXMAABJ0AAASdAHeZh94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\nTkSuQmCC", "text/plain": [ "plot without title" ] }, "metadata": { "image/png": { "height": 600, "width": 1200 } }, "output_type": "display_data" } ], "source": [ "textaes <- data.frame(y = c(7),\n", " x = as.Date(c('2022-06-08')),\n", " lab = c(\"Topic Subscriptions AB Test deployed\"),\n", " size = 30,\n", " face = \"bold\"\n", " )\n", "\n", " p <- notifications_sent_byday %>% \n", " filter(time_sent >= \"2022-05-19\" & time_sent <= \"2022-06-30\") %>% \n", " ggplot(aes(x= time_sent, y = avg_daily_notifications)) +\n", " geom_line(size = 2, color = 'steelblue2') +\n", " geom_vline(xintercept = as.Date('2022-06-02'), linetype = 'dashed', size = 1) +\n", " geom_text(mapping = aes(y = y, x = x, label = lab), \n", " data = textaes, inherit.aes = FALSE, size = 4) +\n", " scale_x_date(date_labels = \"%d-%b\", date_breaks = \"1 week\", minor_breaks = NULL) +\n", " scale_y_continuous(limits = c(0,10))+\n", " labs (y = \"Average number of notifications sent per user\",\n", " x = \"Date\",\n", " title = \"Average daily topic notifications per user across all participating Wikipedias\") +\n", " theme(\n", " panel.grid.minor = element_blank(),\n", " panel.background = element_blank(),\n", " plot.title = element_text(hjust = 0.5),\n", " text = element_text(size=16),\n", " legend.position=\"bottom\",\n", " axis.line = element_line(colour = \"black\")) \n", "\n", "p\n", "ggsave(\"Figures/avg_daily_topic_notifications.png\", p, width = 16, height = 11, units = \"in\", dpi = 300)" ] }, { "cell_type": "code", "execution_count": 71, "id": "45809345-ced5-41e2-a085-79455e222746", "metadata": {}, "outputs": [ { "data": { "text/plain": [ " time_sent avg_daily_notifications\n", " Min. :2022-06-02 Min. :2.828 \n", " 1st Qu.:2022-06-15 1st Qu.:3.495 \n", " Median :2022-06-29 Median :3.981 \n", " Mean :2022-06-29 Mean :4.344 \n", " 3rd Qu.:2022-07-12 3rd Qu.:5.053 \n", " Max. :2022-07-26 Max. :9.547 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# After deployment\n", "notifications_sent_byday %>%\n", "filter(time_sent >= '2022-06-02') %>% # following deployment of the test\n", "summary()" ] }, { "cell_type": "code", "execution_count": 72, "id": "90227b9b-1c38-4eb8-bc06-6a5314f79795", "metadata": {}, "outputs": [ { "data": { "text/plain": [ " time_sent avg_daily_notifications\n", " Min. :2021-06-28 Min. : 1.000 \n", " 1st Qu.:2021-09-21 1st Qu.: 2.653 \n", " Median :2021-12-14 Median : 3.312 \n", " Mean :2021-12-14 Mean : 3.702 \n", " 3rd Qu.:2022-03-08 3rd Qu.: 4.397 \n", " Max. :2022-06-01 Max. :20.194 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Pre deployment\n", "notifications_sent_byday %>%\n", "filter(time_sent < '2022-06-02') %>% # following deployment of the test\n", "summary()" ] }, { "cell_type": "markdown", "id": "11e026a3-27e2-4bf3-9dab-314fcd5c6469", "metadata": {}, "source": [ "The average number of notifications sent per day has remained fairly stable following the deployment of the AB test with a daily average of about 4 notifications per user per day." ] }, { "cell_type": "markdown", "id": "a7be2eb7-a137-4458-9c28-deb7a7e8e4b2", "metadata": {}, "source": [ "### Percent Change Calculation" ] }, { "cell_type": "code", "execution_count": 79, "id": "04fac275-23ad-4753-a352-161a6daa1dba", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'pre_post', 'notification_user' (override with `.groups` argument)\n", "\n", "`summarise()` ungrouping output (override with `.groups` argument)\n", "\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\n", "
A tibble: 2 × 2
pre_postavg_daily_notifications
<chr><dbl>
post4.216718
pre 3.668076
\n" ], "text/latex": [ "A tibble: 2 × 2\n", "\\begin{tabular}{ll}\n", " pre\\_post & avg\\_daily\\_notifications\\\\\n", " & \\\\\n", "\\hline\n", "\t post & 4.216718\\\\\n", "\t pre & 3.668076\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 2 × 2\n", "\n", "| pre_post <chr> | avg_daily_notifications <dbl> |\n", "|---|---|\n", "| post | 4.216718 |\n", "| pre | 3.668076 |\n", "\n" ], "text/plain": [ " pre_post avg_daily_notifications\n", "1 post 4.216718 \n", "2 pre 3.668076 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "notificaiton_sent_pct_change <- notifications_sent %>%\n", " filter(time_sent >= \"2022-05-19\" & time_sent <= \"2022-06-16\") %>% #two weeks before and after\n", " mutate(pre_post = ifelse(time_sent < '2022-06-02', 'pre', 'post')) %>%\n", " group_by(pre_post,notification_user, time_sent) %>%\n", " summarise(n_notifications = sum(num_notifications)) %>%\n", " group_by(pre_post) %>%\n", " summarise(avg_daily_notifications = mean(n_notifications))\n", "\n", "notificaiton_sent_pct_change" ] }, { "cell_type": "markdown", "id": "dd6edc3a-f19d-45a6-89a2-cd4794313845", "metadata": {}, "source": [ "The average daily notification have increase from about 3.6 to 4.2 notifications per contributor day following the AB test (16% increase). This 16% increase does not indicate disruption but shows an expected increase due to use of the new feature." ] }, { "cell_type": "markdown", "id": "1817adca-ef55-43f0-a3b1-dae08790081f", "metadata": {}, "source": [ "## B) Sharp increase in the percent of contributors that disable notifications.\n", "\n", "### Method #1: PrefUpdate\n", "Data Source: We first reviewed data logged in [PrefUpdate](https://schema.wikimedia.org/#!//secondary/jsonschema/analytics/legacy/prefupdate) to determine any signficant changes in the number of contributors that disable notifications two weeks before and after the debployment of the AB test on participating wikis. \n", "\n", "\n", "There are two topic notification preferences: \n", "* 'discussiontools-topicsubscription'. (Enable topic subscription setting)\n", "* 'discussiontools-autotopicsub' (Automatically subscribe to topics setting)\n", "\n", "Notes:\n", "* Properties should be set to either \"0\" or \"1\" to indicate current status; however, a review of the dataset shows some instances being logged at TRUE and FALASE.\n", "* PrefUpdate logs whether the change is from or to a default value. It is unclear how this is handled in an AB test where the defaults was adjusted for each group.\n" ] }, { "cell_type": "code", "execution_count": 257, "id": "331676e9-c9dd-45b1-ae5a-9ca94a38a226", "metadata": {}, "outputs": [], "source": [ "query <- \n", "\"\n", "SELECT\n", "event.savetimestamp as save_time,\n", "event.property AS pref_type,\n", "wiki AS wiki,\n", "event.userid AS pref_user,\n", "event.value AS value,\n", "MIN(event.bucketedusereditcount) AS user_experience,\n", "COUNT(*) AS n_times\n", "FROM \n", "event.prefupdate\n", "WHERE\n", "year = 2022\n", "AND month >= 05\n", "AND event.property IN ('discussiontools-topicsubscription', 'discussiontools-autotopicsub')\n", "-- only at participating wikis\n", "AND wiki IN ('amwiki', 'arzwiki', 'bnwiki', 'eswiki', 'fawiki', 'frwiki', 'hewiki', 'hiwiki', 'idwiki', 'itwiki', 'jawiki', \n", " 'kowiki', 'nlwiki', 'omwiki', 'plwiki', 'ptwiki', 'thwiki',\n", " 'ukwiki', 'viwiki','zhwiki')\n", "-- only logged in users\n", "AND useragent.is_bot = false\n", "GROUP BY\n", "event.savetimestamp,\n", "event.property,\n", "wiki,\n", "event.userid,\n", "event.value\n", "\"\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 258, "id": "2084f970-f611-430c-af0f-b91bfac4d9aa", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Don't forget to authenticate with Kerberos using kinit\n", "\n" ] } ], "source": [ "sub_pref_changes <- wmfdata::query_hive(query)" ] }, { "cell_type": "code", "execution_count": 259, "id": "42f773fa-ca30-4338-94e9-a100744d3595", "metadata": {}, "outputs": [], "source": [ "# convert time sent to date time\n", "sub_pref_changes$save_time <- as.Date(as.character(sub_pref_changes$save_time), format = \"%Y%m%d%H%M%S\")" ] }, { "cell_type": "code", "execution_count": 261, "id": "84d7c769-0493-4152-aa3e-9636363a42eb", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` regrouping output by 'pre_post', 'pref_type' (override with `.groups` argument)\n", "\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A grouped_df: 7 × 4
pre_postpref_typevaluen_users_pref
<chr><chr><chr><int>
postdiscussiontools-autotopicsub 0 3
postdiscussiontools-autotopicsub true 23
postdiscussiontools-topicsubscription\"0\" 1
postdiscussiontools-topicsubscription1 2
postdiscussiontools-topicsubscriptionfalse20
pre discussiontools-autotopicsub 0 9
pre discussiontools-topicsubscriptionfalse 9
\n" ], "text/latex": [ "A grouped\\_df: 7 × 4\n", "\\begin{tabular}{llll}\n", " pre\\_post & pref\\_type & value & n\\_users\\_pref\\\\\n", " & & & \\\\\n", "\\hline\n", "\t post & discussiontools-autotopicsub & 0 & 3\\\\\n", "\t post & discussiontools-autotopicsub & true & 23\\\\\n", "\t post & discussiontools-topicsubscription & \"0\" & 1\\\\\n", "\t post & discussiontools-topicsubscription & 1 & 2\\\\\n", "\t post & discussiontools-topicsubscription & false & 20\\\\\n", "\t pre & discussiontools-autotopicsub & 0 & 9\\\\\n", "\t pre & discussiontools-topicsubscription & false & 9\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A grouped_df: 7 × 4\n", "\n", "| pre_post <chr> | pref_type <chr> | value <chr> | n_users_pref <int> |\n", "|---|---|---|---|\n", "| post | discussiontools-autotopicsub | 0 | 3 |\n", "| post | discussiontools-autotopicsub | true | 23 |\n", "| post | discussiontools-topicsubscription | \"0\" | 1 |\n", "| post | discussiontools-topicsubscription | 1 | 2 |\n", "| post | discussiontools-topicsubscription | false | 20 |\n", "| pre | discussiontools-autotopicsub | 0 | 9 |\n", "| pre | discussiontools-topicsubscription | false | 9 |\n", "\n" ], "text/plain": [ " pre_post pref_type value n_users_pref\n", "1 post discussiontools-autotopicsub 0 3 \n", "2 post discussiontools-autotopicsub true 23 \n", "3 post discussiontools-topicsubscription \"0\" 1 \n", "4 post discussiontools-topicsubscription 1 2 \n", "5 post discussiontools-topicsubscription false 20 \n", "6 pre discussiontools-autotopicsub 0 9 \n", "7 pre discussiontools-topicsubscription false 9 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sub_pref_changes_bytype <- sub_pref_changes %>%\n", " filter(save_time >= \"2022-05-19\" & save_time <= \"2022-06-16\") %>% #two weeks before and after\n", " mutate(pre_post = ifelse(save_time < '2022-06-02', 'pre', 'post')) %>%\n", " group_by(pre_post, pref_type, value) %>%\n", " summarise(n_users_pref = n_distinct(pref_user))\n", "\n", "sub_pref_changes_bytype" ] }, { "cell_type": "markdown", "id": "9d3f0a16-de21-48df-bfdd-b2e9d3231d14", "metadata": {}, "source": [ "There have been no significant changes in the percent of contributors that have disabled the feature looking at either of the possible values in PrefUpdate (0 or false). " ] }, { "cell_type": "markdown", "id": "1ab4b5a0-0719-4aea-af22-382eb2157cf8", "metadata": {}, "source": [ "## Method 2: User Property Table\n", "\n", "Since it is difficult to discern the values using pref update, we next used to the [user property](https://www.mediawiki.org/wiki/Manual:User_properties_table/en?useskin=vector-2022) table to determine the current preference settings of users that have received a notification.\n", "\n", "I used the `sub_created` date logged in the [discussiontools_subscription table](https://www.mediawiki.org/wiki/Extension:DiscussionTools/discussiontools_subscription_table?useskin=vector-2022)to determine the percent of users that subscribed to either a manual or automatic notification before or after the AB test and then disabled it. " ] }, { "cell_type": "markdown", "id": "0b7cb506-8f58-4add-9044-95cc811ec419", "metadata": {}, "source": [ "### Manual Topic Subscriptions\n", "\n", "Notes:\n", "*The automatic topic subscription preference is only recorded when the user turns on the preference. It does not appear when it is disabled. \n", "* The manual topic subscription preference is not recorded when the user opts into the beta preference as it is enabled by default. It only shows when disabled." ] }, { "cell_type": "code", "execution_count": 112, "id": "94e9922b-aa6f-46cb-aaee-60c95a45561b", "metadata": {}, "outputs": [], "source": [ "notifications_users_disabled <-\n", " read.csv(\n", " file = 'Data/notification_users_disabled_manual.csv',\n", " header = TRUE,\n", " sep = \",\",\n", " stringsAsFactors = FALSE\n", " ) # loads notification data" ] }, { "cell_type": "code", "execution_count": 113, "id": "305d1643-6c60-43ad-a73e-91a94504446e", "metadata": {}, "outputs": [], "source": [ "# convert time sent to date time\n", "notifications_users_disabled$sub_created <- as.Date(as.character(notifications_users_disabled$sub_created), format = \"%Y%m%d%H%M%S\")" ] }, { "cell_type": "code", "execution_count": 117, "id": "2cc90991-ad3f-4528-9d98-8475504a4d1c", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` ungrouping output (override with `.groups` argument)\n", "\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\n", "
A tibble: 2 × 4
pre_postnotification_userstopic_disabledpct_disabled
<chr><int><int><chr>
post 88800%
pre 125390.72%
\n" ], "text/latex": [ "A tibble: 2 × 4\n", "\\begin{tabular}{llll}\n", " pre\\_post & notification\\_users & topic\\_disabled & pct\\_disabled\\\\\n", " & & & \\\\\n", "\\hline\n", "\t post & 888 & 0 & 0\\% \\\\\n", "\t pre & 1253 & 9 & 0.72\\%\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 2 × 4\n", "\n", "| pre_post <chr> | notification_users <int> | topic_disabled <int> | pct_disabled <chr> |\n", "|---|---|---|---|\n", "| post | 888 | 0 | 0% |\n", "| pre | 1253 | 9 | 0.72% |\n", "\n" ], "text/plain": [ " pre_post notification_users topic_disabled pct_disabled\n", "1 post 888 0 0% \n", "2 pre 1253 9 0.72% " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Find percent of all users that received a notification and disabled the feature\n", "notification_users_disabled_disabled_pct <- notifications_users_disabled %>%\n", " mutate(pre_post = ifelse(sub_created <= '2022-06-02', 'pre', 'post')) %>%\n", " group_by(pre_post) %>%\n", " summarise(notification_users = n(),\n", " topic_disabled = sum(topic_user != \"NaN\"), #disabled if the feature is present\n", " pct_disabled = paste0(round(topic_disabled/notification_users * 100, 2), '%'))\n", "\n", "notification_users_disabled_disabled_pct\n", "\n" ] }, { "cell_type": "markdown", "id": "e368e6f4-5a4a-4b51-92cd-8abbbc9cf0f2", "metadata": {}, "source": [ "Following the deployment of the AB test, there have been 888 users across all participating wikis that have manually subscribed to a topic. None of those users have explicilty disabled that preference as of the end of the AB test (15 July 2022).\n", "\n", "In comparison, 0.72% of users that manually subscribed to a topic on participating wikis prior to the AB test disabled that preference." ] }, { "cell_type": "markdown", "id": "c5c2a349-dae5-447e-88b9-0c5b42e05554", "metadata": {}, "source": [ "### Automatic topic subscriptions\n", "\n", "Note: The automatic topic subscription preference is only recorded when the user turns on the preference. It does not appear when it is disabled. " ] }, { "cell_type": "code", "execution_count": 119, "id": "2b7d67ad-6c8f-449e-9102-427587b3dd67", "metadata": {}, "outputs": [], "source": [ "notifications_users_disabled_auto <-\n", " read.csv(\n", " file = 'Data/notification_users_disabled_auto.csv',\n", " header = TRUE,\n", " sep = \",\",\n", " stringsAsFactors = FALSE\n", " ) # loads notification data" ] }, { "cell_type": "code", "execution_count": 121, "id": "2b4c840a-2616-4762-8816-e98639689086", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "`summarise()` ungrouping output (override with `.groups` argument)\n", "\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\n", "
A tibble: 1 × 4
pre_postauto_subscribersauto_disabledpct_disabled
<chr><int><int><dbl>
post68213519.79472
\n" ], "text/latex": [ "A tibble: 1 × 4\n", "\\begin{tabular}{llll}\n", " pre\\_post & auto\\_subscribers & auto\\_disabled & pct\\_disabled\\\\\n", " & & & \\\\\n", "\\hline\n", "\t post & 682 & 135 & 19.79472\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 1 × 4\n", "\n", "| pre_post <chr> | auto_subscribers <int> | auto_disabled <int> | pct_disabled <dbl> |\n", "|---|---|---|---|\n", "| post | 682 | 135 | 19.79472 |\n", "\n" ], "text/plain": [ " pre_post auto_subscribers auto_disabled pct_disabled\n", "1 post 682 135 19.79472 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "auto_topic_subscribers_disabled_pct <- notifications_users_disabled_auto %>%\n", " mutate(pre_post = ifelse(sub_created <= '2022-06-02', 'pre', 'post')) %>%\n", " group_by(pre_post) %>%\n", " summarise(auto_subscribers = n(),\n", " auto_disabled = sum(auto_user == \"NaN\"),\n", " pct_disabled = auto_disabled/auto_subscribers * 100)\n", "\n", "auto_topic_subscribers_disabled_pct" ] }, { "cell_type": "markdown", "id": "978b0193-a364-4201-9ff0-dc0c2afdf81a", "metadata": {}, "source": [ "About 19% of users on participating wikis that were autosubscribed to a topic following the deployment of the AB test disabled the feature. \n", "\n", "No users in the AB test were automatically subscribed to a topic prior to the deployment of the AB test; however, this percentage is only slightly higher then the overall rates of users that disabled the automatic topic notification preference found in the adoption metrics report (18%). " ] }, { "cell_type": "markdown", "id": "977a02a4-8258-470f-acd7-5cf331f3954a", "metadata": {}, "source": [ "# Guardrail #2: Average time between when a new comment or new topic is published and someone responding to said comment or topic" ] }, { "cell_type": "markdown", "id": "8c6fa84b-c5b4-41eb-8d58-78abf684b886", "metadata": {}, "source": [ "As observed in the response times identified in the KPI section above, we did not observe any sharp increase in the the average time it takes for people to respond to comments and new topics that are posted to wikitext talk pages. The median response time in the test group was 57% faster than the median response time in the control group. Additionally, there was few long (over 10 day) response times in the test group compared to the control group.\n", "\n", "We did observe a few experience level groups (Senior Contributors) and wikis where there was a higher median response time to comments and topics posted in the test group compared to the control group. Further investigation is needed to help clarfiy the source of these differences.\n", "\n", "Please see KPI section for additional details. " ] }, { "cell_type": "markdown", "id": "73d94607-cff5-4ea6-9cf7-a80249bc22ab", "metadata": {}, "source": [ "# Guardrail #3: Percent change in the number of Senior Contributors making edits to talk page\n", "\n", "Topic Subscriptions should not cause a significant (read: sharp) increase or decrease in the number of Senior Contributors editing talk pages.\n", "\n", "For this analysis, we conducted a pre and post deployment analysis to determine any signficant changes in the number of contributors that started an edit to a talk page on the wikis where the AB test was deployed. Since we are including events logged prior to the AB test, we did not limit data to just the AB test but all edit attempts logged before and after deployment." ] }, { "cell_type": "code", "execution_count": 204, "id": "982b10b8-e350-4456-be0f-44c8599e49f9", "metadata": {}, "outputs": [], "source": [ "query <-\n", "\"SELECT\n", "date_format(dt, 'yyyy-MM-dd') as attempt_dt,\n", "event.user_id,\n", "wiki,\n", "COUNT(*) as n_edits\n", "FROM\n", "event.editattemptstep\n", "WHERE\n", "Year = 2022\n", "AND month >= 05 --look at some time prior and post deployment of the AB test\n", "AND event.action = 'init'\n", "AND useragent.is_bot = false\n", "-- review all talk namespaces\n", " AND event.page_ns % 2 = 1\n", " AND event.platform = 'desktop'\n", " AND event.action = 'init'\n", "-- review participating wikis list\n", " AND wiki IN ('amwiki', 'arzwiki', 'bnwiki', 'eswiki', 'fawiki', 'frwiki', 'hewiki', 'hiwiki', 'idwiki', 'itwiki', 'jawiki', \n", " 'kowiki', 'nlwiki', 'omwiki', 'plwiki', 'ptwiki', 'thwiki',\n", " 'ukwiki', 'viwiki','zhwiki')\n", "-- only logged in users\n", " AND event.user_id != 0 \n", " AND event.user_editcount > 500 -- only senior editrs\n", "GROUP BY\n", "date_format(dt, 'yyyy-MM-dd'),\n", "event.user_id,\n", "wiki\n", "\"" ] }, { "cell_type": "code", "execution_count": null, "id": "cc37fe3f-1f2a-4b78-aa0b-8e2f0da3a738", "metadata": {}, "outputs": [], "source": [ "senior_contributor_edits <- wmfdata::query_hive(query)" ] }, { "cell_type": "code", "execution_count": 206, "id": "02df686c-90a1-4783-926b-c4eb0d982245", "metadata": {}, "outputs": [], "source": [ "# convert time sent to date time\n", "senior_contributor_edits$attempt_dt <- as.Date(senior_contributor_edits$attempt_dt, format = \"%Y-%m-%d\")" ] }, { "cell_type": "code", "execution_count": 207, "id": "79b3d25f-e007-4222-a89c-ba02686f81ce", "metadata": {}, "outputs": [], "source": [ "senior_contributor_daily_edits <- senior_contributor_edits %>%\n", " group_by(attempt_dt) %>%\n", " summarise(n_users = n_distinct(user_id), .groups = 'drop')" ] }, { "cell_type": "code", "execution_count": 209, "id": "7e7d52a7-a9f0-4347-9a91-f8b85165c7ba", "metadata": {}, "outputs": [ { "ename": "ERROR", "evalue": "Error: Unknown graphics device ''\n", "output_type": "error", "traceback": [ "Error: Unknown graphics device ''\nTraceback:\n", "1. ggsave(\"Figures/senior_contributor_daily_edits\", p, width = 16, \n . height = 8, units = \"in\", dpi = 300)", "2. plot_dev(device, filename, dpi = dpi)", "3. abort(glue(\"Unknown graphics device '{device}'\"))", "4. signal_abort(cnd)" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAACWAAAASwCAIAAADwxubWAAAACXBIWXMAABJ0AAASdAHeZh94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\nAAAAAIA+5P8AvSDoGUDEnTgAAAAASUVORK5CYII=", "text/plain": [ "plot without title" ] }, "metadata": { "image/png": { "height": 600, "width": 1200 } }, "output_type": "display_data" } ], "source": [ "# Plot edit completion rates for each user on each wiki \n", "\n", "\n", "textaes <- data.frame(y = 750,\n", " x = as.Date('2022-06-15'),\n", " lab = \"Topic subscriptions AB test deployed\")\n", "\n", "p <- senior_contributor_daily_edits %>%\n", " filter(attempt_dt < '2022-07-18') %>% #end of AB test\n", " ggplot(aes(x= attempt_dt, y = n_users)) +\n", " geom_line(size = 1.5,color = \"steelblue2\") +\n", " geom_vline(xintercept = as.Date('2022-06-02'), linetype = 'dashed', size = 1) +\n", " scale_x_date(date_labels = \"%d-%b\", date_breaks = \"2 weeks\", minor_breaks = NULL) +\n", " scale_y_continuous(limit = c(0, 750)) +\n", " geom_text(mapping = aes(y = y, x = x, label = lab), \n", " data = textaes, inherit.aes = FALSE, size = 5) +\n", " labs (y = \"Number of distinct senior contributors\",\n", " x = \"Date of edit\",\n", " title = \"Number of distinct senior contributor talk page edit attempts \\n across all participating AB test Wikipedias\"\n", " )+\n", " theme(\n", " panel.grid.minor = element_blank(),\n", " panel.background = element_blank(),\n", " plot.title = element_text(hjust = 0.5),\n", " text = element_text(size=18),\n", " legend.position=\"bottom\",\n", " axis.line = element_line(colour = \"black\")) \n", "\n", "p \n", "ggsave(\"Figures/senior_contributor_daily_edits\", p, width = 16, height = 8, units = \"in\", dpi = 300)" ] }, { "cell_type": "markdown", "id": "636e4e01-290e-4762-9a27-d47320175aa4", "metadata": {}, "source": [ "### Percent change calculation" ] }, { "cell_type": "code", "execution_count": 210, "id": "2f72412d-dd44-4c5d-9cc2-490fe222cdfa", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\n", "
A tibble: 2 × 2
pre_postn_users
<chr><int>
post3035
pre 3054
\n" ], "text/latex": [ "A tibble: 2 × 2\n", "\\begin{tabular}{ll}\n", " pre\\_post & n\\_users\\\\\n", " & \\\\\n", "\\hline\n", "\t post & 3035\\\\\n", "\t pre & 3054\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 2 × 2\n", "\n", "| pre_post <chr> | n_users <int> |\n", "|---|---|\n", "| post | 3035 |\n", "| pre | 3054 |\n", "\n" ], "text/plain": [ " pre_post n_users\n", "1 post 3035 \n", "2 pre 3054 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "senior_contributor_pct_change <- senior_contributor_edits %>%\n", " filter(attempt_dt >= \"2022-05-19\" & attempt_dt <= \"2022-06-16\") %>% #two weeks before and after\n", " mutate(pre_post = ifelse(attempt_dt < '2022-06-02', 'pre', 'post')) %>%\n", " group_by(pre_post) %>%\n", " summarise(n_users = n_distinct(user_id), .groups = 'drop')\n", "\n", "senior_contributor_pct_change" ] }, { "cell_type": "markdown", "id": "e7744cd3-24a2-4d0f-ba14-979e7aa71cde", "metadata": {}, "source": [ "Before and after the AB test deployment, we only see less than a 1% decrease in the number of distinct senior contributors." ] }, { "cell_type": "markdown", "id": "102a2ba3-bdea-44d4-8c16-92ce7543f01b", "metadata": {}, "source": [ "## By Wiki" ] }, { "cell_type": "code", "execution_count": 211, "id": "8227d797-0887-4690-bb11-ffe42b7e036e", "metadata": {}, "outputs": [], "source": [ "senior_contributor_daily_edits_wiki <- senior_contributor_edits %>%\n", " group_by(wiki, attempt_dt) %>%\n", " summarise(n_users = n_distinct(user_id), .groups = 'drop')" ] }, { "cell_type": "code", "execution_count": 212, "id": "3d8ffed2-a6e5-4adf-b62c-2c94446a6020", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 18 × 3
wikipostpre
<chr><int><int>
arzwiki 2 3
bnwiki 32 35
eswiki 337332
fawiki 91103
frwiki 624621
hewiki 226224
hiwiki 7 6
idwiki 54 38
itwiki 386374
jawiki 286298
kowiki 57 41
nlwiki 177200
plwiki 204198
ptwiki 131136
thwiki 28 25
ukwiki 111109
viwiki 58 58
zhwiki 225255
\n" ], "text/latex": [ "A tibble: 18 × 3\n", "\\begin{tabular}{lll}\n", " wiki & post & pre\\\\\n", " & & \\\\\n", "\\hline\n", "\t arzwiki & 2 & 3\\\\\n", "\t bnwiki & 32 & 35\\\\\n", "\t eswiki & 337 & 332\\\\\n", "\t fawiki & 91 & 103\\\\\n", "\t frwiki & 624 & 621\\\\\n", "\t hewiki & 226 & 224\\\\\n", "\t hiwiki & 7 & 6\\\\\n", "\t idwiki & 54 & 38\\\\\n", "\t itwiki & 386 & 374\\\\\n", "\t jawiki & 286 & 298\\\\\n", "\t kowiki & 57 & 41\\\\\n", "\t nlwiki & 177 & 200\\\\\n", "\t plwiki & 204 & 198\\\\\n", "\t ptwiki & 131 & 136\\\\\n", "\t thwiki & 28 & 25\\\\\n", "\t ukwiki & 111 & 109\\\\\n", "\t viwiki & 58 & 58\\\\\n", "\t zhwiki & 225 & 255\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 18 × 3\n", "\n", "| wiki <chr> | post <int> | pre <int> |\n", "|---|---|---|\n", "| arzwiki | 2 | 3 |\n", "| bnwiki | 32 | 35 |\n", "| eswiki | 337 | 332 |\n", "| fawiki | 91 | 103 |\n", "| frwiki | 624 | 621 |\n", "| hewiki | 226 | 224 |\n", "| hiwiki | 7 | 6 |\n", "| idwiki | 54 | 38 |\n", "| itwiki | 386 | 374 |\n", "| jawiki | 286 | 298 |\n", "| kowiki | 57 | 41 |\n", "| nlwiki | 177 | 200 |\n", "| plwiki | 204 | 198 |\n", "| ptwiki | 131 | 136 |\n", "| thwiki | 28 | 25 |\n", "| ukwiki | 111 | 109 |\n", "| viwiki | 58 | 58 |\n", "| zhwiki | 225 | 255 |\n", "\n" ], "text/plain": [ " wiki post pre\n", "1 arzwiki 2 3\n", "2 bnwiki 32 35\n", "3 eswiki 337 332\n", "4 fawiki 91 103\n", "5 frwiki 624 621\n", "6 hewiki 226 224\n", "7 hiwiki 7 6\n", "8 idwiki 54 38\n", "9 itwiki 386 374\n", "10 jawiki 286 298\n", "11 kowiki 57 41\n", "12 nlwiki 177 200\n", "13 plwiki 204 198\n", "14 ptwiki 131 136\n", "15 thwiki 28 25\n", "16 ukwiki 111 109\n", "17 viwiki 58 58\n", "18 zhwiki 225 255" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "senior_contributor_pct_change_wiki <- senior_contributor_edits %>%\n", " filter(attempt_dt >= \"2022-05-19\" & attempt_dt <= \"2022-06-16\") %>% #two weeks before and after\n", " mutate(pre_post = ifelse(attempt_dt < '2022-06-02', 'pre', 'post')) %>%\n", " group_by( wiki, pre_post) %>%\n", " summarise(n_users = n_distinct(user_id), .groups = 'drop') %>%\n", " pivot_wider(names_from = pre_post, values_from = n_users)%>%\n", " arrange(wiki)\n", "\n", "senior_contributor_pct_change_wiki" ] }, { "cell_type": "markdown", "id": "af9a1626-f4a1-4c3c-a665-1b9421c96c32", "metadata": {}, "source": [ "There were no signficant changes in the number of senior contributors on a per wiki basis." ] } ], "metadata": { "kernelspec": { "display_name": "R", "language": "R", "name": "ir" }, "language_info": { "codemirror_mode": "r", "file_extension": ".r", "mimetype": "text/x-r-source", "name": "R", "pygments_lexer": "r", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 5 }