rating_analysis.ipynb

{
 "cells": [
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-14T20:01:35.814215Z",
     "start_time": "2024-06-14T20:01:35.810982Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import os\n",
    "from FilmCollector import Film_collector\n",
    "import asyncio\n",
    "import nest_asyncio\n",
    "from matplotlib import pyplot as plt\n",
    "import json\n",
    "from Utils import predict_reviews\n",
    "from matplotlib import ticker"
   ],
   "id": "eb55148f8c738f29",
   "outputs": [],
   "execution_count": 26
  },
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2024-06-14T20:01:35.819382Z",
     "start_time": "2024-06-14T20:01:35.815585Z"
    }
   },
   "source": [
    "\n",
    "def dataframe_split(df_predicated):\n",
    "    df_left = df_predicated[df_predicated['politics'] == 'left']\n",
    "    df_right = df_predicated[df_predicated['politics'] == 'right']\n",
    "    df_neutral = df_predicated[df_predicated['politics'] == 'neutral']\n",
    "    df_left_1 = df_left[df_left['rating'] == 1]\n",
    "    df_left_1.loc[:, 'politics'] = 'left 1'\n",
    "    df_left_10 = df_left[df_left['rating'] == 10]\n",
    "    df_left_10.loc[:, 'politics'] = 'left 10'\n",
    "    df_right_1 = df_right[df_right['rating'] == 1]\n",
    "    df_right_1.loc[:, 'politics'] = 'right 1'\n",
    "    df_right_10 = df_right[df_right['rating'] == 10]\n",
    "    df_right_10.loc[:, 'politics'] = 'right 10'\n",
    "    df_right_filtered = df_right[~df_right['rating'].isin([1, 10])]\n",
    "    df_left_filtered = df_left[~df_left['rating'].isin([1, 10])]\n",
    "    \n",
    "    df_concatenated = pd.concat([\n",
    "        df_neutral,\n",
    "        df_right_filtered,\n",
    "        df_left_filtered,\n",
    "        df_left_1,\n",
    "        df_left_10,\n",
    "        df_right_1,\n",
    "        df_right_10,\n",
    "    ], ignore_index=True)\n",
    "    \n",
    "    df_concatenated = df_concatenated.dropna(subset=['rating'])\n",
    "    return df_concatenated"
   ],
   "outputs": [],
   "execution_count": 27
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-14T20:01:35.827488Z",
     "start_time": "2024-06-14T20:01:35.820140Z"
    }
   },
   "cell_type": "code",
   "source": [
    "def list_folders(directory):\n",
    "    return [name for name in os.listdir(directory) if os.path.isdir(os.path.join(directory, name))]\n",
    "\n",
    "folder_path = 'Data'  \n",
    "folders = list_folders(folder_path)\n",
    "print(folders)"
   ],
   "id": "d5d9a34f7ffff2a0",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['tt0097216', 'tt0892769', 'tt5672290', 'tt0395169', 'tt0249462', 'tt6133466', 'tt7713068', 'tt0286716', 'tt0093300', 'tt13975458', 'tt0068334', 'tt12262202', 'tt1785612', 'tt0145487', 'tt11003218', 'tt10676048', 'tt0103923', 'tt3480822', 'tt8075192', 'tt0364569', 'tt12037194', 'tt3169706', 'tt1206885']\n"
     ]
    }
   ],
   "execution_count": 28
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-14T20:01:36.042975Z",
     "start_time": "2024-06-14T20:01:35.828845Z"
    }
   },
   "cell_type": "code",
   "source": [
    "nest_asyncio.apply()\n",
    "collector = Film_collector()\n",
    "\n",
    "async def get_film_data(imdb_id):\n",
    "    return await collector.get_all(imdb_id, False, False)\n",
    "\n",
    "async def process_films():\n",
    "    results = []\n",
    "    for film_link in folders:\n",
    "        data = await get_film_data(film_link)\n",
    "        results.append(data)\n",
    "    return results\n",
    "\n",
    "film_datas = asyncio.get_event_loop().run_until_complete(process_films())\n"
   ],
   "id": "66677eab7e45befd",
   "outputs": [],
   "execution_count": 29
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-14T20:01:36.046377Z",
     "start_time": "2024-06-14T20:01:36.043674Z"
    }
   },
   "cell_type": "code",
   "source": [
    "def compute_ratings(films):\n",
    "    neutral_diff_ = []\n",
    "    left_right_neutral_diff_ = []\n",
    "    all_diff_ = []\n",
    "    for film in films:\n",
    "        film_data, film_rev = film \n",
    "        split = dataframe_split(predict_reviews(film_rev))\n",
    "        df_split_neutral = split[split['politics'] == 'neutral']\n",
    "        df_split_left_right_neutral = split[split['politics'].isin(['left', 'right', 'neutral'])]\n",
    "        df_all = split\n",
    "        mean_rating_neutral = df_split_neutral['rating'].mean()\n",
    "        mean_rating_left_right_neutral = df_split_left_right_neutral['rating'].mean()\n",
    "        mean_rating_all = df_all['rating'].mean()\n",
    "        film_data = json.loads(film_data)\n",
    "        rating_value = film_data['rating']['ratingValue']\n",
    "        neutral_diff_.append(rating_value - mean_rating_neutral)\n",
    "        left_right_neutral_diff_.append(rating_value - mean_rating_left_right_neutral)\n",
    "        all_diff_.append(rating_value - mean_rating_all)\n",
    "    return neutral_diff_, left_right_neutral_diff_, all_diff_"
   ],
   "id": "d754a9bf1f8a252e",
   "outputs": [],
   "execution_count": 30
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-14T20:03:13.716731Z",
     "start_time": "2024-06-14T20:01:36.047198Z"
    }
   },
   "cell_type": "code",
   "source": [
    "\n",
    "def distribution_difference_rating(film_diff):\n",
    "    neutral_diff, left_right_neutral_diff, all_diff = compute_ratings(film_diff)\n",
    "    data = [neutral_diff, left_right_neutral_diff, all_diff]\n",
    "    \n",
    "    mean_neutral_diff = sum(neutral_diff) / len(neutral_diff)\n",
    "    mean_left_right_neutral_diff = sum(left_right_neutral_diff) / len(left_right_neutral_diff)\n",
    "    mean_all_diff = sum(all_diff) / len(all_diff)\n",
    "    \n",
    "    complete_mean = (mean_neutral_diff + mean_left_right_neutral_diff + mean_all_diff) / 3\n",
    "    labels = ['Neutral', 'Left/Right/Neutral', 'All']\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    ax = plt.gca() \n",
    "    ax.yaxis.set_major_locator(ticker.MaxNLocator(10))\n",
    "    ax.yaxis.set_minor_locator(ticker.AutoMinorLocator(10)) \n",
    "    \n",
    "    sns.boxplot(data=data)\n",
    "    plt.xticks(ticks=range(len(labels)), labels=labels)\n",
    "    \n",
    "    plt.axhline(y=complete_mean, color='r', linestyle='--', label=f'Mean of all differences: {complete_mean:.2f}')\n",
    "    plt.title('Comparison of Differences with the IMDB rating')\n",
    "    plt.ylabel('Differences to IMDB rating')\n",
    "    plt.legend() \n",
    "    plt.show()\n",
    "\n",
    "non_political_film = [] \n",
    "\n",
    "for film in film_datas:\n",
    "    film_data, film_rev = film\n",
    "    film_d = json.loads(film_data)\n",
    "\n",
    "\n",
    "    if film_d.get('political_m', True): \n",
    "        continue  \n",
    "    else:\n",
    "        print(film_d['name'])\n",
    "        non_political_film.append(film)  \n",
    "\n",
    "distribution_difference_rating(non_political_film)"
   ],
   "id": "8f5327ee33ac1883",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "How to Train Your Dragon\n",
      "The First Omen\n",
      "Hulk\n",
      "Jaws: The Revenge\n",
      "Cube: Ichido haittara, saigo\n",
      "The Acolyte\n",
      "Spider-Man\n",
      "Pig\n",
      "The Marvels\n",
      "Captain America\n",
      "Manbiki kazoku\n",
      "Oldeuboi\n",
      "Furiosa: A Mad Max Saga\n",
      "Rambo: Last Blood\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 31
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-14T20:04:07.076961Z",
     "start_time": "2024-06-14T20:03:13.717691Z"
    }
   },
   "cell_type": "code",
   "source": [
    "\n",
    "political_film = []\n",
    "\n",
    "for film in film_datas:\n",
    "    film_data, film_rev = film\n",
    "    film_d = json.loads(film_data)\n",
    "\n",
    "    if film_d.get('political_m', False):\n",
    "        print(film_d['name'])\n",
    "        political_film.append(film)\n",
    "\n",
    "distribution_difference_rating(political_film)\n"
   ],
   "id": "e2b6cf8d3fce3c63",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Do the Right Thing\n",
      "Hotel Rwanda\n",
      "Billy Elliot\n",
      "The First Purge\n",
      "Birds of Prey and the Fantabulous Emancipation of One Harley Quinn\n",
      "The Candidate\n",
      "The Punk Singer\n",
      "Black Widow\n",
      "Pride\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 32
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}