{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cross-toner",
   "metadata": {},
   "source": [
    "# CASE STUDY 6B: Burst Detection of Documents using Textnets "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "checked-choice",
   "metadata": {},
   "source": [
    "<img src=\"https://ithaka-labs.s3.amazonaws.com/static-files/images/tdm/tdmdocs/CC_BY.png\" align=left alt=\"CC BY license logo\" /><br /><br />\n",
    "Created by [Manika Lamba](http://manika-lamba.github.io) under [Creative Commons CC BY License](https://creativecommons.org/licenses/by/4.0/)<br />\n",
    "**For questions/comments, email lambamanika07@gmail.com**<br />\n",
    "____"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "accepting-nurse",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "\"package 'aRxiv' was built under R version 3.6.3\""
     ]
    }
   ],
   "source": [
    "#Load libraries\n",
    "library(aRxiv)\n",
    "library(bursts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "religious-wisconsin",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "retrieved batch 1\n",
      "retrieved batch 2\n",
      "retrieved batch 3\n",
      "retrieved batch 4\n"
     ]
    }
   ],
   "source": [
    "data <- arxiv_search('abs:\"burst detection\"', limit=1000)\n",
    "write.csv(data, \"6b_dataset.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "classical-reserve",
   "metadata": {},
   "outputs": [],
   "source": [
    "bursts <- kleinberg(as.POSIXct(data$submitted))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "supposed-testimony",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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j4rIEgvpyEbJJpvCCb7IL30Lii3WUfzDaHkHyTzZz9aoWWmOMLLNkgvd13hNISo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\n4D/QLy/8p+IqFAAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Accumulation of submissions\n",
    "plot(as.POSIXct(data$submitted),\n",
    "     1:length(as.POSIXct(data$submitted)),\n",
    "     xlab='Time',\n",
    "     ylab='Submissions')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "naughty-vaccine",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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v4nwvkBIV2Mw5B+bR8vPSy3f25Lut09\nflqedAevmpAuxmFIy/Vm9frnYrN52G6tl8PDaXfxignpYhyG9O9u6+n189th/by1Hm5PuH/X\nTUgX48NjpM3+n+9PjnMabvmLIaRz5pa/GN+HdLr9YssBuBjfhXTraYYTE9LF+C6kf4bF42az\n8mTDyQjpYnwX0mb3gtKweDrZ3l07IV2Mb0Pa/mbDcKejkxESBIQEASFBQEgQEBIEhAQBIUFA\nSBAQEgSEBAEhQUBIEBASBIQEASFBQEgQEBIEhAQBIUFASBAQEgSEBAEhQUBIEBASBIQEASFB\nQEgQEBIEhAQBIUHgf6YKnldtw2AbAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Bursts in submissions\n",
    "plot(bursts, xaxt = 'n')\n",
    "axis.POSIXct(1, bursts$start)"
   ]
  }
 ],
 "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": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}