T301884-rejection-reasons-graphs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "bc27151e",
   "metadata": {},
   "source": [
    "# Rejection Reasons Graphs\n",
    "\n",
    "This notebook accompanies the Python notebook, and uses `ggplot` to make some nice graphs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5305567d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "── \u001b[1mAttaching packages\u001b[22m ─────────────────────────────────────── tidyverse 1.3.0 ──\n",
      "\n",
      "\u001b[32m✔\u001b[39m \u001b[34mggplot2\u001b[39m 3.3.2     \u001b[32m✔\u001b[39m \u001b[34mpurrr  \u001b[39m 0.3.4\n",
      "\u001b[32m✔\u001b[39m \u001b[34mtibble \u001b[39m 3.0.4     \u001b[32m✔\u001b[39m \u001b[34mdplyr  \u001b[39m 1.0.2\n",
      "\u001b[32m✔\u001b[39m \u001b[34mtidyr  \u001b[39m 1.1.2     \u001b[32m✔\u001b[39m \u001b[34mstringr\u001b[39m 1.4.0\n",
      "\u001b[32m✔\u001b[39m \u001b[34mreadr  \u001b[39m 1.4.0     \u001b[32m✔\u001b[39m \u001b[34mforcats\u001b[39m 0.5.0\n",
      "\n",
      "── \u001b[1mConflicts\u001b[22m ────────────────────────────────────────── tidyverse_conflicts() ──\n",
      "\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mfilter()\u001b[39m masks \u001b[34mstats\u001b[39m::filter()\n",
      "\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mlag()\u001b[39m    masks \u001b[34mstats\u001b[39m::lag()\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(tidyverse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7653fe96",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Give me wider plots, please\n",
    "options(repr.plot.width = 14, repr.plot.height = 7)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "758feadd",
   "metadata": {},
   "source": [
    "Make platform be a comprehensible string, add log edit count and then turn that into a bucket by flooring it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "5930ac39",
   "metadata": {},
   "outputs": [],
   "source": [
    "rejection_reasons <- read_csv('datasets/rejection-reasons-2022-03-04.csv',\n",
    "                              col_types = 'clci') %>%\n",
    "    mutate(platform = ifelse(is_mobile, 'mobile', 'desktop'),\n",
    "           log_tagged_edit_count = log2(1 + tagged_edit_count),\n",
    "           tagged_edit_count_bucket = floor(log_tagged_edit_count))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "abf27c0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
       "  0.000   1.000   2.585   2.651   4.248   7.983 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "summary(rejection_reasons$log_tagged_edit_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2a6f7410",
   "metadata": {},
   "outputs": [],
   "source": [
    "head(rejection_reasons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "050db171",
   "metadata": {},
   "outputs": [],
   "source": [
    "rejection_reasons %>%\n",
    "    filter(wiki == 'bnwiki') %>%\n",
    "    group_by(platform, tagged_edit_count_bucket, rejection_reason) %>%\n",
    "    tally() %>%\n",
    "    mutate(per_group = sum(n)) %>%\n",
    "    ungroup() %>%\n",
    "    mutate(perc = 100 * n / per_group, prob = n / per_group)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "82c6fc6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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M+ZZYBuEEADtC6ABmjB1Q4DvWbJ8Z2dxy9ZEyYKdE6wsspLLmdcURWc7p9XJaf7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QDK2LI9K/+QaoEsNQBd27xGfPK/5VADtk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\nD5QAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 840,
       "width": 720
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.width = 12, repr.plot.height = 14)\n",
    "rejection_reasons %>%\n",
    "    group_by(wiki, platform, rejection_reason) %>%\n",
    "    tally() %>%\n",
    "    mutate(per_group = sum(n)) %>%\n",
    "    ungroup() %>%\n",
    "    mutate(perc = 100 * n / per_group, prob = n / per_group) %>%\n",
    "    ggplot(aes(x = rejection_reason, y = perc)) +\n",
    "        labs(title = 'Rejection reasons') +\n",
    "        geom_col(position = 'dodge2') +\n",
    "        facet_grid(wiki ~ platform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "a07157cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Qvef9vknd805tjQ7qkDw3sBOoUAGqBtATRAJ3XDuXMr7+zaGT+MjVQAWj6ABmhb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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 840,
       "width": 720
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.width = 12, repr.plot.height = 14)\n",
    "rejection_reasons %>%\n",
    "    group_by(platform, tagged_edit_count_bucket, rejection_reason) %>%\n",
    "    tally() %>%\n",
    "    mutate(per_group = sum(n)) %>%\n",
    "    ungroup() %>%\n",
    "    mutate(perc = 100 * n / per_group, prob = n / per_group) %>%\n",
    "    ggplot(aes(x = rejection_reason, y = perc)) +\n",
    "        labs(title = 'Rejection reasons') +\n",
    "        geom_col(position = 'dodge2') +\n",
    "        facet_grid(tagged_edit_count_bucket ~ platform)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35895ba2",
   "metadata": {},
   "source": [
    "## Saving Graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "f722c85e",
   "metadata": {},
   "outputs": [],
   "source": [
    "for(wiki_db in unique(rejection_reasons$wiki)) {\n",
    "    rejection_reasons %>%\n",
    "        filter(wiki == wiki_db) %>%\n",
    "        group_by(platform, tagged_edit_count_bucket, rejection_reason) %>%\n",
    "        tally() %>%\n",
    "        mutate(per_group = sum(n)) %>%\n",
    "        ungroup() %>%\n",
    "        mutate(perc = 100 * n / per_group, prob = n / per_group) %>%\n",
    "        ggplot(aes(x = rejection_reason, y = perc)) +\n",
    "            labs(title = paste(wiki_db, '– Rejection reasons')) +\n",
    "            geom_col(position = 'dodge2') +\n",
    "            facet_grid(tagged_edit_count_bucket ~ platform)\n",
    "    ggsave(paste0('rejection-reasons-platform-tenure-', wiki_db, '.png'), path = 'graphs',\n",
    "           width = 12, height = 14, units = \"in\", dpi = \"screen\")\n",
    "    }"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7a45ff4",
   "metadata": {},
   "source": [
    "It turned out that these didn't reveal much. There's an indication that users move away from using \"Other\" as their experience grows. We also have few data points for more experienced users.\n",
    "\n",
    "Suggested next step:\n",
    "\n",
    "* Loosen the restriction on data, let's look at user behaviour across the first four weeks after registration.\n",
    "\n",
    "If that doesn't give us much more interesting patterns, we'll wrap up what we have.\n",
    "\n",
    "## Loosened Time Restriction\n",
    "\n",
    "It didn't give us a lot more information. We get some signal in the form of more experienced users being able to make edits, however it didn't significantly change things. At this point, I think providing an overview table of number and percentage of rejections split by platform makes most sense, although the reasons are going to be very similar across both of them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "91451724",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A tibble: 9 × 6</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>platform</th><th scope=col>rejection_reason</th><th scope=col>n</th><th scope=col>per_group</th><th scope=col>perc</th><th scope=col>prob</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>desktop</td><td>everyday        </td><td>2732</td><td>5155</td><td>52.997090</td><td>0.52997090</td></tr>\n",
       "\t<tr><td>desktop</td><td>more-fewer-words</td><td> 378</td><td>5155</td><td> 7.332687</td><td>0.07332687</td></tr>\n",
       "\t<tr><td>desktop</td><td>other           </td><td> 668</td><td>5155</td><td>12.958293</td><td>0.12958293</td></tr>\n",
       "\t<tr><td>desktop</td><td>wrong-target    </td><td>1377</td><td>5155</td><td>26.711930</td><td>0.26711930</td></tr>\n",
       "\t<tr><td>mobile </td><td>everyday        </td><td>1835</td><td>3443</td><td>53.296544</td><td>0.53296544</td></tr>\n",
       "\t<tr><td>mobile </td><td>more-fewer-words</td><td> 271</td><td>3443</td><td> 7.871043</td><td>0.07871043</td></tr>\n",
       "\t<tr><td>mobile </td><td>other           </td><td> 484</td><td>3443</td><td>14.057508</td><td>0.14057508</td></tr>\n",
       "\t<tr><td>mobile </td><td>undefined       </td><td>  62</td><td>3443</td><td> 1.800755</td><td>0.01800755</td></tr>\n",
       "\t<tr><td>mobile </td><td>wrong-target    </td><td> 791</td><td>3443</td><td>22.974150</td><td>0.22974150</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 9 × 6\n",
       "\\begin{tabular}{llllll}\n",
       " platform & rejection\\_reason & n & per\\_group & perc & prob\\\\\n",
       " <chr> & <chr> & <int> & <int> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t desktop & everyday         & 2732 & 5155 & 52.997090 & 0.52997090\\\\\n",
       "\t desktop & more-fewer-words &  378 & 5155 &  7.332687 & 0.07332687\\\\\n",
       "\t desktop & other            &  668 & 5155 & 12.958293 & 0.12958293\\\\\n",
       "\t desktop & wrong-target     & 1377 & 5155 & 26.711930 & 0.26711930\\\\\n",
       "\t mobile  & everyday         & 1835 & 3443 & 53.296544 & 0.53296544\\\\\n",
       "\t mobile  & more-fewer-words &  271 & 3443 &  7.871043 & 0.07871043\\\\\n",
       "\t mobile  & other            &  484 & 3443 & 14.057508 & 0.14057508\\\\\n",
       "\t mobile  & undefined        &   62 & 3443 &  1.800755 & 0.01800755\\\\\n",
       "\t mobile  & wrong-target     &  791 & 3443 & 22.974150 & 0.22974150\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 9 × 6\n",
       "\n",
       "| platform &lt;chr&gt; | rejection_reason &lt;chr&gt; | n &lt;int&gt; | per_group &lt;int&gt; | perc &lt;dbl&gt; | prob &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| desktop | everyday         | 2732 | 5155 | 52.997090 | 0.52997090 |\n",
       "| desktop | more-fewer-words |  378 | 5155 |  7.332687 | 0.07332687 |\n",
       "| desktop | other            |  668 | 5155 | 12.958293 | 0.12958293 |\n",
       "| desktop | wrong-target     | 1377 | 5155 | 26.711930 | 0.26711930 |\n",
       "| mobile  | everyday         | 1835 | 3443 | 53.296544 | 0.53296544 |\n",
       "| mobile  | more-fewer-words |  271 | 3443 |  7.871043 | 0.07871043 |\n",
       "| mobile  | other            |  484 | 3443 | 14.057508 | 0.14057508 |\n",
       "| mobile  | undefined        |   62 | 3443 |  1.800755 | 0.01800755 |\n",
       "| mobile  | wrong-target     |  791 | 3443 | 22.974150 | 0.22974150 |\n",
       "\n"
      ],
      "text/plain": [
       "  platform rejection_reason n    per_group perc      prob      \n",
       "1 desktop  everyday         2732 5155      52.997090 0.52997090\n",
       "2 desktop  more-fewer-words  378 5155       7.332687 0.07332687\n",
       "3 desktop  other             668 5155      12.958293 0.12958293\n",
       "4 desktop  wrong-target     1377 5155      26.711930 0.26711930\n",
       "5 mobile   everyday         1835 3443      53.296544 0.53296544\n",
       "6 mobile   more-fewer-words  271 3443       7.871043 0.07871043\n",
       "7 mobile   other             484 3443      14.057508 0.14057508\n",
       "8 mobile   undefined          62 3443       1.800755 0.01800755\n",
       "9 mobile   wrong-target      791 3443      22.974150 0.22974150"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rejection_reasons %>%\n",
    "    group_by(platform, rejection_reason) %>%\n",
    "    tally() %>%\n",
    "    mutate(per_group = sum(n)) %>%\n",
    "    ungroup() %>%\n",
    "    mutate(perc = 100 * n / per_group, prob = n / per_group)"
   ]
  }
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