From 0a67e6cf0b1ae716f74b285c40f98ff16ba02443 Mon Sep 17 00:00:00 2001 From: Lyudmila Vaseva <vaseva@mi.fu-berlin.de> Date: Sat, 20 Jul 2019 12:20:59 +0200 Subject: [PATCH] Plot reverts on Wikipedia until April 2017 --- src/explore.ipynb | 1188 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 1188 insertions(+) diff --git a/src/explore.ipynb b/src/explore.ipynb index 5c55348..a1e8c27 100644 --- a/src/explore.ipynb +++ b/src/explore.ipynb @@ -17309,6 +17309,1194 @@ " 921 427 Possible Emergency Reponse Needed" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Reverts on Wikipedia" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here is an attempt to investigate the overall number of reverts on Wikipedia over time and compare them with the filter hits over time patterns. Is the peak of the filter hits mirrored in general revert activity on Wikipedia?\n", + "\n", + "The dataset used comes from Geiger and Halfaker: https://github.com/halfak/are-the-bots-really-fighting, more precisely I plot here their revert dataset for EN Wikipedia https://github.com/halfak/are-the-bots-really-fighting/blob/master/datasets/monthly_bot_reverts/enwiki_20170420.tsv" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>month</th>\n", + " <th>page_namespace</th>\n", + " 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0 1 0 0 \n", + "2 2001-10-01 0 8 0 0 \n", + "3 2001-10-01 1 1 0 0 \n", + "4 2001-10-01 2 6 0 0 \n", + "5 2001-10-01 4 1 0 0 \n", + "6 2001-10-01 5 1 0 0 \n", + "7 2001-11-01 0 70 0 0 \n", + "8 2001-11-01 1 1 0 0 \n", + "9 2001-11-01 2 11 0 0 \n", + "10 2001-11-01 4 16 0 0 \n", + "11 2001-11-01 5 3 0 0 \n", + "12 2001-11-01 100 3 0 0 \n", + "13 2001-12-01 0 248 3 1 \n", + "14 2001-12-01 1 5 0 0 \n", + "15 2001-12-01 2 12 0 0 \n", + "16 2001-12-01 3 3 0 0 \n", + "17 2001-12-01 4 14 0 0 \n", + "18 2001-12-01 12 1 0 0 \n", + "19 2001-12-01 100 3 1 0 \n", + "20 2002-01-01 0 124 0 0 \n", + "21 2002-01-01 1 7 0 0 \n", + "22 2002-01-01 2 1 0 0 \n", + "23 2002-01-01 3 2 0 0 \n", + "24 2002-01-01 4 9 0 0 \n", + "25 2002-01-01 12 2 0 0 \n", + "26 2002-01-01 100 1 0 0 \n", + "27 2002-02-01 0 69 3 2 \n", + "28 2002-02-01 1 1 0 0 \n", + "29 2002-02-01 2 8 0 0 \n", + "... ... ... ... ... ... \n", + "3456 2017-03-01 108 5 0 0 \n", + "3457 2017-03-01 109 9 4 4 \n", + "3458 2017-03-01 118 485 115 19 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+ "df_reverts = pd.read_csv(\"reverts_enwiki_20170420.tsv\", sep='\\t')\n", + "df_reverts['month'] = pd.to_datetime(df_reverts['month'], format=\"%Y%m%d\")\n", + "df_reverts" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " page_namespace reverts bot_reverts bot_reverteds \\\n", + "month \n", + "2001-07-01 0 1 0 0 \n", + "2001-08-01 0 1 0 0 \n", + "2001-10-01 12 17 0 0 \n", + "2001-11-01 112 104 0 0 \n", + "2001-12-01 122 286 4 1 \n", + "2002-01-01 122 146 0 0 \n", + "2002-02-01 19 83 3 2 \n", + "2002-03-01 22 143 1 1 \n", + "2002-04-01 26 133 1 2 \n", + "2002-05-01 107 109 7 2 \n", + "2002-06-01 7 148 2 6 \n", + "2002-07-01 122 176 10 4 \n", + "2002-08-01 122 375 6 7 \n", + "2002-09-01 115 683 14 10 \n", + "2002-10-01 127 874 37 11 \n", + "2002-11-01 140 1007 3 2 \n", + "2002-12-01 127 1240 0 1 \n", + "2003-01-01 127 1080 0 0 \n", + "2003-02-01 127 1558 0 3 \n", + 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8049 \n", + "2012-12-01 3531 \n", + "2013-01-01 4946 \n", + "2013-02-01 5316 \n", + "2013-03-01 157295 \n", + "2013-04-01 14952 \n", + "2013-05-01 3466 \n", + "2013-06-01 2428 \n", + "2013-07-01 2276 \n", + "2013-08-01 3403 \n", + "2013-09-01 1561 \n", + "2013-10-01 2061 \n", + "2013-11-01 1773 \n", + "2013-12-01 1694 \n", + "2014-01-01 1969 \n", + "2014-02-01 1772 \n", + "2014-03-01 2492 \n", + "2014-04-01 1960 \n", + "2014-05-01 1498 \n", + "2014-06-01 1425 \n", + "2014-07-01 1678 \n", + "2014-08-01 1255 \n", + "2014-09-01 2080 \n", + "2014-10-01 1531 \n", + "2014-11-01 1597 \n", + "2014-12-01 1313 \n", + "2015-01-01 1898 \n", + "2015-02-01 1643 \n", + "2015-03-01 1831 \n", + "2015-04-01 1530 \n", + "2015-05-01 1658 \n", + "2015-06-01 2052 \n", + "2015-07-01 3493 \n", + "2015-08-01 2798 \n", + "2015-09-01 2079 \n", + "2015-10-01 3309 \n", + "2015-11-01 1676 \n", + "2015-12-01 1913 \n", + "2016-01-01 1792 \n", + "2016-02-01 1386 \n", + "2016-03-01 2099 \n", + "2016-04-01 2689 \n", + "2016-05-01 2175 \n", + "2016-06-01 1576 \n", + "2016-07-01 2638 \n", + "2016-08-01 1948 \n", + "2016-09-01 1351 \n", + "2016-10-01 1418 \n", + "2016-11-01 2395 \n", + "2016-12-01 2171 \n", + "2017-01-01 2310 \n", + "2017-02-01 2553 \n", + "2017-03-01 3494 \n", + "2017-04-01 1295 \n" + ] + } + ], + "source": [ + "df_reverts_aggregated = df_reverts.groupby(['month']).sum()\n", + "\n", + "with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n", + " print (df_reverts_aggregated)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<matplotlib.axes._subplots.AxesSubplot at 0x7f2f1a6edd68>" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1080x504 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(15,7))\n", + "df_reverts_aggregated[['reverts', 'bot_reverts']].plot(ax=ax)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ok. So the patterns from 2016 filter activity are not mirrored here. Btw, the spike in March 2013 is the batch action by AddBot removing interwiki links, since these were handled by Wikidata discussed in the intro of Geiger and Halfaker's paper (https://doi.org/10.1145/3134684)" + ] + }, { "cell_type": "markdown", "metadata": {}, -- GitLab