article_talk_editors_stats.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import csv\n",
    "from collections import Counter\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6605"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Talk page usernames\n",
    "csvpath = '/home/michael/school/cprose_research/wp/wikipedia/data/ipc_utf8_talkpages.csv'\n",
    "talk_username_mentions = []\n",
    "\n",
    "with open(csvpath, 'r') as csvfile:\n",
    "    reader = csv.reader(csvfile, delimiter=',')\n",
    "    for row in reader:\n",
    "        talk_username_mentions.append(row[3])\n",
    "\n",
    "talk_counter = Counter(talk_username_mentions)\n",
    "len(talk_counter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "232451"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ARTICLE USERNAMES\n",
    "art_filepath = '/home/michael/school/cprose_research/wp/wikipedia/data/ipc_article_biases.csv'\n",
    "\n",
    "article_usernames = []\n",
    "\n",
    "with open(art_filepath, 'r') as csvfile:\n",
    "    reader = csv.reader(csvfile, delimiter=',')\n",
    "    next(reader)\n",
    "    for row in reader:\n",
    "        article_usernames.append(row[2])\n",
    "\n",
    "article_counter = Counter(article_usernames)\n",
    "len(article_counter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5075"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Editors in both article and talk pages\n",
    "both_usernames = []\n",
    "\n",
    "for name in article_counter.keys():\n",
    "    if name in talk_username_mentions:\n",
    "        both_usernames.append(name)\n",
    "        \n",
    "len(both_usernames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26247"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# See editors w more than 5 edits\n",
    "edit_threshold = 5\n",
    "eds_above_threshold = []\n",
    "\n",
    "for ed in article_counter.keys():\n",
    "    if article_counter[ed] >= edit_threshold:\n",
    "        eds_above_threshold.append(ed)\n",
    "\n",
    "len(eds_above_threshold)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3642"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Editors w more than 5 edits in talk pages\n",
    "both_threshold_usernames = []\n",
    "\n",
    "for name in eds_above_threshold:\n",
    "    if name in both_usernames:\n",
    "        both_threshold_usernames.append(name)\n",
    "        \n",
    "len(both_threshold_usernames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1, 140839),\n",
       " (2, 40619),\n",
       " (3, 15992),\n",
       " (4, 8754),\n",
       " (5, 5163),\n",
       " (6, 3488),\n",
       " (7, 2436),\n",
       " (8, 1845),\n",
       " (9, 1432),\n",
       " (10, 1143),\n",
       " (11, 943),\n",
       " (12, 748),\n",
       " (13, 644),\n",
       " (14, 531),\n",
       " (15, 474),\n",
       " (16, 454),\n",
       " (17, 418),\n",
       " (18, 322),\n",
       " (19, 314),\n",
       " (20, 287),\n",
       " (21, 231),\n",
       " (22, 221),\n",
       " (23, 192),\n",
       " (24, 192),\n",
       " (25, 182),\n",
       " (26, 157),\n",
       " (27, 154),\n",
       " (28, 146),\n",
       " (29, 141),\n",
       " (30, 115),\n",
       " (31, 121),\n",
       " (32, 118),\n",
       " (33, 95),\n",
       " (34, 107),\n",
       " (35, 115),\n",
       " (36, 72),\n",
       " (37, 73),\n",
       " (38, 75),\n",
       " (39, 72),\n",
       " (40, 62)]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of editors for each count numbers\n",
    "article_counts = Counter(article_counter.values())\n",
    "list(article_counts.items())[:40]\n",
    "#list(article_counts.values())[:70]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(345676,)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts = np.asarray(list(article_counter.values()))\n",
    "counts.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python3/dist-packages/matplotlib/figure.py:387: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n",
      "  \"matplotlib is currently using a non-GUI backend, \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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Sbkjl8yQdVFo3QdKSNJ1V5XmamVn1LZRrgTGdygL4RkQcnqafAkgaAZwBjEj7TJWktM81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\nM8vCCcXMzLJwQjEzsyz+P7dZvTwIgpEwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f416a134b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "# Number of article edits stats\n",
    "\n",
    "hbins = range(1,16)\n",
    "plt.hist(counts, bins=hbins)\n",
    "plt.title(\"IPC article editor edit counts\")\n",
    "plt.xlabel(\"# edits\")\n",
    "plt.xlim([1,15])\n",
    "plt.ylabel(\"# users\")\n",
    "fig = plt.gcf()\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "figpath = '/home/michael/school/cprose_research/wp_articles/ipc_article_editor_counts.png'\n",
    "fig.savefig(figpath, dpi=400)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5320"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Stats for editors in both\n",
    "# Will take a long x\n",
    "\n",
    "article_editors_in_both = [mention for mention in article_usernames if mention in both_usernames]\n",
    "both_article_counter = Counter(article_editors_in_both)\n",
    "len(both_article_counter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "489\n",
      "347\n",
      "250\n",
      "238\n",
      "167\n",
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      "14\n",
      "15\n",
      "12\n"
     ]
    }
   ],
   "source": [
    "both_article_counts = Counter(both_article_counter.values())\n",
    "#list(both_article_counts.items())[:40]\n",
    "#for count in list(both_article_counts.values())[:70]:\n",
    "#     print(count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python3/dist-packages/matplotlib/figure.py:387: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n",
      "  \"matplotlib is currently using a non-GUI backend, \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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r3w/YOLDYRrowkSRtZ7vOYJ7lVXV/kl8APk/XDPQl4A9msoEkuwOfAc6qqgeSPDqtqipJ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\n4EhZG3ttAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f416a215080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "# Counts of article edits for editors on both article and talk pages\n",
    "\n",
    "hbins = range(1,21)\n",
    "plt.hist(list(both_article_counts.values()), bins=hbins)\n",
    "plt.title(\"IPC article editor edit counts\")\n",
    "plt.xlabel(\"# edits\")\n",
    "plt.xlim([1,20])\n",
    "plt.ylabel(\"# users\")\n",
    "fig = plt.gcf()\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1141"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Look at editors in talk that don't do article edits\n",
    "talk_no_article = [name for name in talk_counter.keys() if name not in both_usernames]\n",
    "len(talk_no_article)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1, 762),\n",
       " (2, 223),\n",
       " (3, 68),\n",
       " (4, 33),\n",
       " (5, 20),\n",
       " (6, 8),\n",
       " (7, 6),\n",
       " (40, 1),\n",
       " (9, 3),\n",
       " (10, 3),\n",
       " (11, 1),\n",
       " (12, 1),\n",
       " (66, 1),\n",
       " (14, 2),\n",
       " (13, 1),\n",
       " (27, 1),\n",
       " (8, 3),\n",
       " (15, 1),\n",
       " (230, 1),\n",
       " (29, 1),\n",
       " (37, 1)]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "talk_no_article_mentions = [name for name in talk_username_mentions if name in talk_no_article]\n",
    "talk_no_article_counter = Counter(talk_no_article_mentions)\n",
    "talk_no_article_counts = Counter(list(talk_no_article_counter.values()))\n",
    "list(talk_no_article_counts.items())[:30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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