Analyses/Wordnet-Affect.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot WordNet Affect usage\n",
    "\n",
    "WordNet affect counts and dominance scores are precomputed. We provide the dominance scores for making the plots. To obtain WordNet domains, please see here: https://wndomains.fbk.eu/download.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"../Data/wn-peer-mhp.tsv\") as f:\n",
    "    lines = f.read().strip().split('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('DISGUST', 1.71028997750357),\n",
       " ('SURPRISE', 1.3983259978898),\n",
       " ('ANGER', 1.14086998542706),\n",
       " ('FEAR', 1.06922731579117),\n",
       " ('SADNESS', 1.06749537047073),\n",
       " ('JOY', 1.00660420378226)]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from operator import itemgetter\n",
    "\n",
    "cat2score = {}\n",
    "for l in lines:\n",
    "    parts = l.split('\\t')\n",
    "    cat = parts[0]\n",
    "    score = parts[1]  \n",
    "    cat2score[cat] = float(score)\n",
    "cat2score_sorted = sorted(cat2score.items(), key=itemgetter(1), reverse=True)\n",
    "\n",
    "cat2score_sorted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "matplotlib.rcParams.update({\n",
    "    'font.family': 'serif',\n",
    "    'font.size': 20\n",
    "})\n",
    "\n",
    "fig, axs = plt.subplots(1, 1, figsize=(12, 8), sharey=False)\n",
    "axs.set_title('WordNet dominance scores (Peer / MHP)')\n",
    "\n",
    "xticklabels, bars = zip(*cat2score_sorted)\n",
    "xticks = range(1, len(bars) + 1)\n",
    "yticks = [i/10 for i in range(int((min(bars) - .1) * 10), int((max(bars) + .1) * 10), 1)]\n",
    "\n",
    "axs.set_xticks(range(1, len(bars) + 1), minor=False)\n",
    "axs.set_xticklabels(xticklabels, minor=False)\n",
    "\n",
    "axs.bar(range(1, len(bars) + 1), bars, color='#422e9e')\n",
    "axs.grid(axis='y', alpha=0.7, color='lavender')\n",
    "axs.axhline(y=1, linewidth=4, color='red')\n",
    "\n",
    "\n",
    "fig.autofmt_xdate(rotation=45)\n",
    "\n",
    "bar_coordinates = [(x, y) for x,y in zip(xticks, bars)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "coordinates { \n",
      "\t(DISGUST,1.71028997750357)\n",
      "\t(SURPRISE,1.3983259978898)\n",
      "\t(ANGER,1.14086998542706)\n",
      "\t(FEAR,1.06922731579117)\n",
      "\t(SADNESS,1.06749537047073)\n",
      "\t(JOY,1.00660420378226)\n",
      "};\n",
      "symbolic x coords=(DISGUST,SURPRISE,ANGER,FEAR,SADNESS,JOY)\n",
      "ytick={0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7}\n"
     ]
    }
   ],
   "source": [
    "coordinates = \"\\n\".join([f\"\\t({label},{y})\" for (x,y), label in zip(bar_coordinates, xticklabels)])\n",
    "print(f\"coordinates {'{'} \\n{coordinates}\\n{'};'}\")\n",
    "\n",
    "xcoords=\",\".join(xticklabels)\n",
    "print(f\"symbolic x coords=({xcoords})\")\n",
    "\n",
    "print(f\"ytick={'{'}{str(yticks)[1:-1]}{'}'}\")"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "0aff92935e087d4f18a34a5240c96bf6ffa876757752d2f8d58f2dbe375e5d2c"
  },
  "kernelspec": {
   "display_name": "Python 3.9.7 ('st')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}