Movie_Review_Sentiment_Analysis_and_Recommendation_System.ipynb

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  "metadata": {
    "colab": {
      "name": "Movie Review Sentiment Analysis and Recommendation System.ipynb",
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      "mount_file_id": "1t9DyJbHl6_etY5m3DRpR4eNXiXEmLUd5",
      "authorship_tag": "ABX9TyMQyJ/bsEp+GHkBdg/TnQhA",
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ljsonnanburg/Movie-Recommendation-System/blob/main/Movie_Review_Sentiment_Analysis_and_Recommendation_System.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ExtghbDMKk79"
      },
      "source": [
        "# Web Scraper\n",
        "\n",
        "Below is our scraper to make a a series of API requests from IMDB and collect data for our project. Our example data set uses the top 1000 most popular movies based on recent activity on IMDB. To summarize what it's doing:\n",
        "Given a page of movie search results found through https://www.imdb.com/search/title/?ref_=fn_asr_tt, it collects general data about the movie and and about one \"helpful positive\", one \"helpful negative\", one \"unhelpful positive\", and one \"unhelpful negative\" review."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mgpypdcSZGe6"
      },
      "source": [
        "import requests\n",
        "from bs4 import BeautifulSoup\n",
        "import re\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import itertools"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7kFvO1yLhhVn"
      },
      "source": [
        "# Function for mass soup production\n",
        "def createSoup(url):\n",
        "    r = requests.get(url)\n",
        "    data = r.text\n",
        "    \n",
        "    return BeautifulSoup(data)\n",
        "#soup = createSoup('https://www.imdb.com/search/title/?groups=top_1000&languages=en')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7xiLCsmalWTv"
      },
      "source": [
        "# Finding Movies"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7oJKCpB6hhYH"
      },
      "source": [
        "# expects soup of movie search results url\n",
        "def find_movie_tags(soup):\n",
        "  # Movies have a tags with class None\n",
        "  # Finding all such tags\n",
        "  movie_tags = soup.find_all('a', attrs={'class': None})\n",
        "  # List comprehension voodoo to filter just the tags that fit the pattern of movie urls, ex: <a href=\"/title/tt11083552/?ref_=adv_li_i\">\n",
        "  movie_tags = [tag.attrs['href'] for tag in movie_tags if tag.attrs['href'].startswith('/title') & tag.attrs['href'].endswith('/')]\n",
        "\n",
        "  # Removing duplicates\n",
        "  movie_tags = list(set(movie_tags))\n",
        "  return movie_tags"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sMmezSYOo8EH"
      },
      "source": [
        "# Fetching Reviews\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N-lpclkzhhan"
      },
      "source": [
        "def get_review_pages(movie_tags):\n",
        "  # This takes a while \n",
        "  ordered_reviews_list = [getReviews(tag) for tag in movie_tags] \n",
        "  unpacked_reviews = list(sum(ordered_reviews_list, ()))\n",
        "  return unpacked_reviews"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CTJyRPM38g0l"
      },
      "source": [
        "# Returns indicies for high and low ratings \n",
        "def highsAndLows(a):\n",
        "  high = a.index(max(a))\n",
        "  low = a.index(min(a))\n",
        "  return high, low\n",
        "\n",
        "# pass tags from movie_tags\n",
        "def firstPageReviews(tag):\n",
        "  url = 'https://www.imdb.com' + tag + 'reviews'\n",
        "  soup = createSoup(url)\n",
        "  # Get list of star ratings\n",
        "  user_review_ratings = [tag.previous_element for tag in \n",
        "                           soup.find_all('span', attrs={'class': 'point-scale'})]\n",
        "  # Get review tags\n",
        "  user_review_tags = soup.find_all('a', attrs={'class':'title'})\n",
        "  #print(user_review_tags)\n",
        "\n",
        "  # Finds indices for highest and lowest ratings \n",
        "  high_ind, low_ind = highsAndLows(list(map(int, user_review_ratings)))\n",
        "  #high_ind = user_review_ratings.index(max(user_review_ratings))\n",
        "  #low_ind = user_review_ratings.index(min(user_review_ratings))\n",
        "\n",
        "  # Get tags for positive and negative reviews\n",
        "  pos_tag = user_review_tags[high_ind]\n",
        "  neg_tag = user_review_tags[low_ind]\n",
        "    \n",
        "  #print(pos_tag['href'])\n",
        "  # return the negative and positive review link\n",
        "  pos_link = 'https://www.imdb.com' + pos_tag['href']\n",
        "  neg_link = 'https://www.imdb.com' + neg_tag['href']\n",
        "\n",
        "  return pos_link, neg_link\n",
        "\n",
        "# Returns VERY HIGH and VERY LOW ratings. Presumably these will always be 10/10, 1/10, and very 'unhelpful'.\n",
        "def bestWorst(tag):\n",
        "  best_url = 'https://www.imdb.com' + tag + 'reviews?sort=userRating&dir=desc&ratingFilter=0'\n",
        "  best_soup = createSoup(best_url)\n",
        "  best_url = 'https://www.imdb.com' + (best_soup.find('a', attrs={'class':'title'}))['href']\n",
        "\n",
        "  worst_url = 'https://www.imdb.com' + tag + 'reviews?sort=userRating&dir=asc&ratingFilter=0'\n",
        "  worst_soup = createSoup(worst_url)\n",
        "  worst_url = 'https://www.imdb.com' + (worst_soup.find('a', attrs={'class':'title'}))['href']\n",
        "\n",
        "  return best_url, worst_url\n",
        "\n",
        "# Returns tuple containing, in order: Helpful high rating, helpful low rating, unhelpful high rating, unhelpful low rating\n",
        "def getReviews(tag):\n",
        "  helpful_high, helpful_low = firstPageReviews(tag)\n",
        "  \n",
        "  high, low = bestWorst(tag)\n",
        "\n",
        "  ordered_reviews = (helpful_high,helpful_low,high,low)\n",
        "  #print(ordered_reviews)\n",
        "  return ordered_reviews"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PlqZX61IL3Jp"
      },
      "source": [
        "# Getting Review Information"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vG-3_6sIhhf2"
      },
      "source": [
        "# returns review text\n",
        "def getText(url):\n",
        "    # Get soup for review's page\n",
        "    soup = createSoup(url)\n",
        "    \n",
        "    # Find review text tag\n",
        "    tag = soup.find('div', attrs={'class': 'text show-more__control'})\n",
        "    \n",
        "    return tag.getText()\n",
        "\n",
        "# returns movie title\n",
        "def getTitle(url):\n",
        "    # Get soup for review's page\n",
        "    soup = createSoup(url)\n",
        "    \n",
        "    # Find title tag\n",
        "    tag = soup.find('h1')\n",
        "    \n",
        "    #print(list(tag.children)[1].getText())\n",
        "    return list(tag.children)[1].getText()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QYljpUmwL8a_"
      },
      "source": [
        "# Getting General Movie Information"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SznnGUOrxSwu"
      },
      "source": [
        "# Takes list of tages from scrape_results_page\n",
        "# returns dataframe of attributes of movies listed on that page\n",
        "def get_movie_data(tag_list):\n",
        "  # initializing lists that later become dataframe\n",
        "  titles_list = []\n",
        "  genres_list = []\n",
        "  plots_list = []\n",
        "  ratings_list = []\n",
        "  # loop to get data from each tag\n",
        "  for tag in tag_list:\n",
        "    # builds url form tag\n",
        "    url = 'https://www.imdb.com' + tag\n",
        "    movie_soup = createSoup(url) # creates soup object for current movie page\n",
        "    # gets genre list\n",
        "    genres = movie_soup.findAll('a', attrs={'class': 'ipc-metadata-list-item__list-content-item ipc-metadata-list-item__list-content-item--link' })\n",
        "\n",
        "    # gets movie title\n",
        "    movie_title = movie_soup.find('h1').text\n",
        "    titles_list.append(movie_title)\n",
        "    \n",
        "    movie_genres = []\n",
        "    for genre in genres:\n",
        "      if('genre' in genre.attrs['href']):\n",
        "        movie_genres.append(genre.text)\n",
        "    \n",
        "    # gets movie rating\n",
        "    movie_rating = movie_soup.find('span', attrs={'class': 'AggregateRatingButton__RatingScore-sc-1il8omz-1 fhMjqK' }).text\n",
        "    ratings_list.append(movie_rating)\n",
        "    # gets text of movie plot\n",
        "    movie_plot = movie_soup('div', attrs={'class': 'ipc-html-content ipc-html-content--base'})[0].text\n",
        "    plots_list.append(movie_plot)\n",
        "    # stringifies genres\n",
        "    movie_genres = ', '.join(movie_genres)\n",
        "    genres_list.append(movie_genres)\n",
        "  \n",
        "  # builds dataframe of data for movies from results page\n",
        "  movie_df = pd.DataFrame({'title': titles_list, 'genre': genres_list, 'plot': plots_list, 'rating': ratings_list})\n",
        "\n",
        "  return(movie_df)\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "#get_movie_data(['/title/tt4016934/'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PSW0L7C4MDNb"
      },
      "source": [
        "# Scraper Function\n",
        "Directs the other functions to scrape data for all searched movie results"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_9P5HLKf877R"
      },
      "source": [
        "# pass this the url of a movie search results page and it does the rest\n",
        "def scrape_results_page(url):\n",
        "  soup = createSoup(url) # creates soup object of search results\n",
        "  movie_tags = soup.find_all('a', attrs={'class': None}) # collects tags that lead to moview urls\n",
        "  # List comprehension voodoo to filter just the tags that fit the pattern of movie urls, e.g.: <a href=\"/title/tt11083552/?ref_=adv_li_i\">\n",
        "  movie_tags = [tag.attrs['href'] for tag in movie_tags if tag.attrs['href'].startswith('/title') & tag.attrs['href'].endswith('/')]\n",
        "\n",
        "  \n",
        "  movie_tags = list(set(movie_tags)) # Removing duplicates\n",
        "  movie_df = get_movie_data(movie_tags) # Retrieves dataframe of movie attributes\n",
        "\n",
        "  unpacked_reviews = get_review_pages(movie_tags) # collects pages of desired reviews\n",
        "  review_texts = [getText(url) for url in unpacked_reviews] # collects text of reviews from those pages\n",
        "  movie_titles = [getTitle(url) for url in unpacked_reviews] # collects titles of the movies reviewed\n",
        "  # this code's gone under so many revisions, I'm pretty sure this is redundant but I'm afraid to change anything because it takes > 1 hour to test\n",
        "  ordered_reviews_list = [getTitle(url) for url in unpacked_reviews] \n",
        "  # generates column of labels for review sentiments\n",
        "  review_sentiment = np.array(['helpful positive', 'helpful negative', 'unhelpful positive', 'unhelpful negative'] * (len(ordered_reviews_list)//4))\n",
        "  # creates dataframe of reviews\n",
        "  review_df = pd.DataFrame({'url': unpacked_reviews, 'title': movie_titles, 'review': review_texts, 'sentiment': review_sentiment})\n",
        "  return review_df, movie_df"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I69a51BqMOEa"
      },
      "source": [
        "# Function Calls\n",
        "Applying the scraper to the top 1000 movies on IMDB. IMDB only shows 250 maximum results on a single page, so we need to call it 4 times."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3vbwPwYK9YUn"
      },
      "source": [
        "# function calls to get data frames for each page of 250 movie listings\n",
        "review_df1, movie_df1 = scrape_results_page('https://www.imdb.com/search/title/?groups=top_1000&count=250')\n",
        "review_df2, movie_df2 = scrape_results_page('https://www.imdb.com/search/title/?groups=top_1000&count=250&start=251&ref_=adv_nxt')\n",
        "review_df3, movie_df3 = scrape_results_page('https://www.imdb.com/search/title/?groups=top_1000&count=250&start=501&ref_=adv_nxt')\n",
        "review_df4, movie_df4 = scrape_results_page('https://www.imdb.com/search/title/?groups=top_1000&count=250&start=751&ref_=adv_nxt')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FW27UiyYMpho"
      },
      "source": [
        "# Constructing the Dataframe"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TvWrjN-IMoUv"
      },
      "source": [
        "# combining all the data\n",
        "df1 = review_df1.merge(movie_df1, left_on='title', right_on='title')\n",
        "df2 = review_df2.merge(movie_df2, left_on='title', right_on='title')\n",
        "df3 = review_df3.merge(movie_df3, left_on='title', right_on='title')\n",
        "df4 = review_df4.merge(movie_df4, left_on='title', right_on='title')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "id": "J8svz4lBNCed",
        "outputId": "f23bc66b-2b38-4832-a583-4b53b4b87374"
      },
      "source": [
        "full_df = df1.append(df2, ignore_index=True).append(df3, ignore_index=True).append(df4, ignore_index=True)\n",
        "full_df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>url</th>\n",
              "      <th>title</th>\n",
              "      <th>review</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>genre</th>\n",
              "      <th>plot</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>https://www.imdb.com/review/rw0213795/</td>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Many people compare \"Once Upon a Time in Ameri...</td>\n",
              "      <td>helpful positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>https://www.imdb.com/review/rw2900651/</td>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>... Directors of all time. Let's start with a ...</td>\n",
              "      <td>helpful negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>https://www.imdb.com/review/rw1324424/</td>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Simply the best movie ever made. Dot.Life. Lov...</td>\n",
              "      <td>unhelpful positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>https://www.imdb.com/review/rw0213775/</td>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Once Upon a Time in America is Sergio Leone's ...</td>\n",
              "      <td>unhelpful negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>https://www.imdb.com/review/rw6164695/</td>\n",
              "      <td>American Psycho</td>\n",
              "      <td>The author of the novel and the director of th...</td>\n",
              "      <td>helpful positive</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3995</th>\n",
              "      <td>https://www.imdb.com/review/rw0293026/</td>\n",
              "      <td>Delicatessen</td>\n",
              "      <td>I'm going to go against what virtually everyon...</td>\n",
              "      <td>unhelpful negative</td>\n",
              "      <td>Comedy, Crime</td>\n",
              "      <td>Centered on a post-apocalyptic society where f...</td>\n",
              "      <td>7.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3996</th>\n",
              "      <td>https://www.imdb.com/review/rw2375880/</td>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>I'll say one thing right off the bat, this mov...</td>\n",
              "      <td>helpful positive</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3997</th>\n",
              "      <td>https://www.imdb.com/review/rw2325862/</td>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>This movie has a message every Brazilian shoul...</td>\n",
              "      <td>helpful negative</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3998</th>\n",
              "      <td>https://www.imdb.com/review/rw4358713/</td>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>There is something so beautiful in the craft t...</td>\n",
              "      <td>unhelpful positive</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3999</th>\n",
              "      <td>https://www.imdb.com/review/rw4311697/</td>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>*** WARNING: Some spoilers follow...Don't beli...</td>\n",
              "      <td>unhelpful negative</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4000 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                         url  ... rating\n",
              "0     https://www.imdb.com/review/rw0213795/  ...    8.4\n",
              "1     https://www.imdb.com/review/rw2900651/  ...    8.4\n",
              "2     https://www.imdb.com/review/rw1324424/  ...    8.4\n",
              "3     https://www.imdb.com/review/rw0213775/  ...    8.4\n",
              "4     https://www.imdb.com/review/rw6164695/  ...    7.6\n",
              "...                                      ...  ...    ...\n",
              "3995  https://www.imdb.com/review/rw0293026/  ...    7.6\n",
              "3996  https://www.imdb.com/review/rw2375880/  ...    8.0\n",
              "3997  https://www.imdb.com/review/rw2325862/  ...    8.0\n",
              "3998  https://www.imdb.com/review/rw4358713/  ...    8.0\n",
              "3999  https://www.imdb.com/review/rw4311697/  ...    8.0\n",
              "\n",
              "[4000 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5bGx5OOkMwFs"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SauYGH4aMvUV"
      },
      "source": [
        "# Saving the Dataframe\n",
        "Because you don't want to need to run this program more than once."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17
        },
        "id": "f1xcPD1rkhyV",
        "outputId": "9d71314c-d4d8-4331-8978-e14ef6604b3d"
      },
      "source": [
        "from google.colab import files\n",
        "full_df.to_csv('IMDB_reviews.csv') \n",
        "files.download('IMDB_reviews.csv') # commented out so it doesn't surprise download on your computer"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "    async function download(id, filename, size) {\n",
              "      if (!google.colab.kernel.accessAllowed) {\n",
              "        return;\n",
              "      }\n",
              "      const div = document.createElement('div');\n",
              "      const label = document.createElement('label');\n",
              "      label.textContent = `Downloading \"${filename}\": `;\n",
              "      div.appendChild(label);\n",
              "      const progress = document.createElement('progress');\n",
              "      progress.max = size;\n",
              "      div.appendChild(progress);\n",
              "      document.body.appendChild(div);\n",
              "\n",
              "      const buffers = [];\n",
              "      let downloaded = 0;\n",
              "\n",
              "      const channel = await google.colab.kernel.comms.open(id);\n",
              "      // Send a message to notify the kernel that we're ready.\n",
              "      channel.send({})\n",
              "\n",
              "      for await (const message of channel.messages) {\n",
              "        // Send a message to notify the kernel that we're ready.\n",
              "        channel.send({})\n",
              "        if (message.buffers) {\n",
              "          for (const buffer of message.buffers) {\n",
              "            buffers.push(buffer);\n",
              "            downloaded += buffer.byteLength;\n",
              "            progress.value = downloaded;\n",
              "          }\n",
              "        }\n",
              "      }\n",
              "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
              "      const a = document.createElement('a');\n",
              "      a.href = window.URL.createObjectURL(blob);\n",
              "      a.download = filename;\n",
              "      div.appendChild(a);\n",
              "      a.click();\n",
              "      div.remove();\n",
              "    }\n",
              "  "
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "download(\"download_edaf2403-2cd1-4437-ae93-6259cbdc51c7\", \"IMDB_reviews.csv\", 9276169)"
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KLMSfm0LUVxW",
        "outputId": "e3c28100-c4c5-453e-f09e-b1a99b4236a2"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "todsVBq3M5B0"
      },
      "source": [
        "# Data Preparation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iv7NkrQ1NI1G"
      },
      "source": [
        "# Reviewdata = full_df # ONLY UNCOMMENT if you want to test all of the above code, otherwise use the provided file\n",
        "\n",
        "# Local directory\n",
        "Reviewdata = pd.read_csv('IMDB_reviews.csv')\n",
        "Reviewdata.drop(['Unnamed: 0', 'url'], axis=1, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dkZLFZMxNfvQ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3ca71e21-a233-4e57-abff-eb41a9c5be12"
      },
      "source": [
        "Reviewdata.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4000, 6)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I0diZrJ4NiR4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "outputId": "96ba64c8-5ca1-40e8-dce8-ece49b228099"
      },
      "source": [
        "Reviewdata.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>title</th>\n",
              "      <th>review</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>genre</th>\n",
              "      <th>plot</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Many people compare \"Once Upon a Time in Ameri...</td>\n",
              "      <td>helpful positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>... Directors of all time. Let's start with a ...</td>\n",
              "      <td>helpful negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Simply the best movie ever made. Dot.Life. Lov...</td>\n",
              "      <td>unhelpful positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Once Upon a Time in America is Sergio Leone's ...</td>\n",
              "      <td>unhelpful negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>The author of the novel and the director of th...</td>\n",
              "      <td>helpful positive</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                         title  ... rating\n",
              "0  Once Upon a Time in America  ...    8.4\n",
              "1  Once Upon a Time in America  ...    8.4\n",
              "2  Once Upon a Time in America  ...    8.4\n",
              "3  Once Upon a Time in America  ...    8.4\n",
              "4              American Psycho  ...    7.6\n",
              "\n",
              "[5 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uctrU4LCNlKn",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "982e2d45-2124-42c6-fe8d-8aac6559d3be"
      },
      "source": [
        "Reviewdata.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 4000 entries, 0 to 3999\n",
            "Data columns (total 6 columns):\n",
            " #   Column     Non-Null Count  Dtype  \n",
            "---  ------     --------------  -----  \n",
            " 0   title      4000 non-null   object \n",
            " 1   review     4000 non-null   object \n",
            " 2   sentiment  4000 non-null   object \n",
            " 3   genre      4000 non-null   object \n",
            " 4   plot       4000 non-null   object \n",
            " 5   rating     4000 non-null   float64\n",
            "dtypes: float64(1), object(5)\n",
            "memory usage: 187.6+ KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Xky7Kpz_NmT3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "outputId": "26a2fd9b-a558-4a8f-db72-ff943eb90d78"
      },
      "source": [
        "Reviewdata.describe().transpose()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>rating</th>\n",
              "      <td>4000.0</td>\n",
              "      <td>7.9566</td>\n",
              "      <td>0.277337</td>\n",
              "      <td>7.6</td>\n",
              "      <td>7.7</td>\n",
              "      <td>7.9</td>\n",
              "      <td>8.1</td>\n",
              "      <td>9.3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         count    mean       std  min  25%  50%  75%  max\n",
              "rating  4000.0  7.9566  0.277337  7.6  7.7  7.9  8.1  9.3"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CAWGlEemNo5E"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k18-KZbPNny3"
      },
      "source": [
        "# Data Cleaning/EDA"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HBnYBWpXN4hx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 250
        },
        "outputId": "63a4f7ea-4176-4b8b-8321-cc8011f61e7c"
      },
      "source": [
        "### Checking Missing values in the Data Set and printing the Percentage for Missing Values for Each Columns ###\n",
        "\n",
        "count = Reviewdata.isnull().sum().sort_values(ascending=False)\n",
        "percentage = ((Reviewdata.isnull().sum()/len(Reviewdata)*100)).sort_values(ascending=False)\n",
        "missing_data = pd.concat([count, percentage], axis=1,\n",
        "keys=['Count','Percentage'])\n",
        "\n",
        "print('Count and percentage of missing values for the columns:')\n",
        "\n",
        "missing_data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Count and percentage of missing values for the columns:\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "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>Count</th>\n",
              "      <th>Percentage</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>rating</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>plot</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>genre</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sentiment</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>review</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>title</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           Count  Percentage\n",
              "rating         0         0.0\n",
              "plot           0         0.0\n",
              "genre          0         0.0\n",
              "sentiment      0         0.0\n",
              "review         0         0.0\n",
              "title          0         0.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ck_m00xIN7JB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 420
        },
        "outputId": "62db73d2-decd-43bc-bbbf-e554197dd5f1"
      },
      "source": [
        "### Checking for the Distribution of Default ###\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "print('Percentage for default\\n')\n",
        "print(round(Reviewdata.sentiment.value_counts(normalize=True)*100,2))\n",
        "#round(Reviewdata.sentiment.value_counts(normalize=True)*100,2).plot(kind='pie')\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "labels= ['Helpful positive', 'Unhelpful positive', 'Helpful negative', 'Unhelpful negative']\n",
        "colors=['blue', 'yellow', 'green', 'orange']\n",
        "sizes= [round(Reviewdata.sentiment.value_counts(normalize=True)*100,2)]\n",
        "\n",
        "plt.pie(sizes,labels=labels, colors=colors, startangle=90, shadow=True,explode=(0.1, 0.1, 0.1, 0.1), autopct='%1.2f%%')\n",
        "plt.title('Percentage Distributions by review type')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Percentage for default\n",
            "\n",
            "unhelpful negative    25.0\n",
            "helpful positive      25.0\n",
            "unhelpful positive    25.0\n",
            "helpful negative      25.0\n",
            "Name: sentiment, dtype: float64\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:13: MatplotlibDeprecationWarning: Non-1D inputs to pie() are currently squeeze()d, but this behavior is deprecated since 3.1 and will be removed in 3.3; pass a 1D array instead.\n",
            "  del sys.path[0]\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ExQlURjpN8TR",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "33594df0-b840-4be7-9fa9-0f8393d02769"
      },
      "source": [
        "import re\n",
        "from string import punctuation\n",
        "from textblob import TextBlob\n",
        "from nltk import stem\n",
        "from nltk.corpus import stopwords\n",
        "import nltk\n",
        "nltk.download('all')\n",
        "from nltk.stem import LancasterStemmer, WordNetLemmatizer, PorterStemmer\n",
        "import sys\n",
        "!{sys.executable} -m pip install autocorrect\n",
        "from autocorrect import Speller"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading collection 'all'\n",
            "[nltk_data]    | \n",
            "[nltk_data]    | Downloading package abc to /root/nltk_data...\n",
            "[nltk_data]    |   Package abc is already up-to-date!\n",
            "[nltk_data]    | Downloading package alpino to /root/nltk_data...\n",
            "[nltk_data]    |   Package alpino is already up-to-date!\n",
            "[nltk_data]    | Downloading package biocreative_ppi to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package biocreative_ppi is already up-to-date!\n",
            "[nltk_data]    | Downloading package brown to /root/nltk_data...\n",
            "[nltk_data]    |   Package brown is already up-to-date!\n",
            "[nltk_data]    | Downloading package brown_tei to /root/nltk_data...\n",
            "[nltk_data]    |   Package brown_tei is already up-to-date!\n",
            "[nltk_data]    | Downloading package cess_cat to /root/nltk_data...\n",
            "[nltk_data]    |   Package cess_cat is already up-to-date!\n",
            "[nltk_data]    | Downloading package cess_esp to /root/nltk_data...\n",
            "[nltk_data]    |   Package cess_esp is already up-to-date!\n",
            "[nltk_data]    | Downloading package chat80 to /root/nltk_data...\n",
            "[nltk_data]    |   Package chat80 is already up-to-date!\n",
            "[nltk_data]    | Downloading package city_database to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package city_database is already up-to-date!\n",
            "[nltk_data]    | Downloading package cmudict to /root/nltk_data...\n",
            "[nltk_data]    |   Package cmudict is already up-to-date!\n",
            "[nltk_data]    | Downloading package comparative_sentences to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package comparative_sentences is already up-to-\n",
            "[nltk_data]    |       date!\n",
            "[nltk_data]    | Downloading package comtrans to /root/nltk_data...\n",
            "[nltk_data]    |   Package comtrans is already up-to-date!\n",
            "[nltk_data]    | Downloading package conll2000 to /root/nltk_data...\n",
            "[nltk_data]    |   Package conll2000 is already up-to-date!\n",
            "[nltk_data]    | Downloading package conll2002 to /root/nltk_data...\n",
            "[nltk_data]    |   Package conll2002 is already up-to-date!\n",
            "[nltk_data]    | Downloading package conll2007 to /root/nltk_data...\n",
            "[nltk_data]    |   Package conll2007 is already up-to-date!\n",
            "[nltk_data]    | Downloading package crubadan to /root/nltk_data...\n",
            "[nltk_data]    |   Package crubadan is already up-to-date!\n",
            "[nltk_data]    | Downloading package dependency_treebank to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package dependency_treebank is already up-to-date!\n",
            "[nltk_data]    | Downloading package dolch to /root/nltk_data...\n",
            "[nltk_data]    |   Package dolch is already up-to-date!\n",
            "[nltk_data]    | Downloading package europarl_raw to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package europarl_raw is already up-to-date!\n",
            "[nltk_data]    | Downloading package floresta to /root/nltk_data...\n",
            "[nltk_data]    |   Package floresta is already up-to-date!\n",
            "[nltk_data]    | Downloading package framenet_v15 to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package framenet_v15 is already up-to-date!\n",
            "[nltk_data]    | Downloading package framenet_v17 to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package framenet_v17 is already up-to-date!\n",
            "[nltk_data]    | Downloading package gazetteers to /root/nltk_data...\n",
            "[nltk_data]    |   Package gazetteers is already up-to-date!\n",
            "[nltk_data]    | Downloading package genesis to /root/nltk_data...\n",
            "[nltk_data]    |   Package genesis is already up-to-date!\n",
            "[nltk_data]    | Downloading package gutenberg to /root/nltk_data...\n",
            "[nltk_data]    |   Package gutenberg is already up-to-date!\n",
            "[nltk_data]    | Downloading package ieer to /root/nltk_data...\n",
            "[nltk_data]    |   Package ieer is already up-to-date!\n",
            "[nltk_data]    | Downloading package inaugural to /root/nltk_data...\n",
            "[nltk_data]    |   Package inaugural is already up-to-date!\n",
            "[nltk_data]    | Downloading package indian to /root/nltk_data...\n",
            "[nltk_data]    |   Package indian is already up-to-date!\n",
            "[nltk_data]    | Downloading package jeita to /root/nltk_data...\n",
            "[nltk_data]    |   Package jeita is already up-to-date!\n",
            "[nltk_data]    | Downloading package kimmo to /root/nltk_data...\n",
            "[nltk_data]    |   Package kimmo is already up-to-date!\n",
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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qz7F8pd7OBsw"
      },
      "source": [
        "# Apply first level cleaning\n",
        "\n",
        "contraction_patterns=[(r'can\\'t', 'can not'),\n",
        "                    (r'haven\\'t', 'have not'),\n",
        "                    (r'wasn\\'t', 'was not'),\n",
        "                    (r'(\\w+)\\'ll', '\\g<1> will'),\n",
        "                    (r'(\\w+)\\'re', '\\g<1> are'),\n",
        "                     (r'don\\'t', 'do not'),\n",
        "                     (r'I\\'m','I am')]\n",
        "\n",
        "class contraction_replacer(object):\n",
        "    def __init__(self, contraction_patterns):        \n",
        "        # store compiled regex object\n",
        "        self._contraction_regexes = [(re.compile(p), replaced_text) for p, replaced_text in contraction_patterns]\n",
        "        \n",
        "    def do_contraction_normalization(self, text):\n",
        "        for contraction_regex, replaced_text in self._contraction_regexes:\n",
        "            text = contraction_regex.sub(replaced_text, text)\n",
        "        return text     \n",
        "\n",
        "sample_contraction_replacer = contraction_replacer(contraction_patterns)\n",
        "\n",
        "#This function converts to lower-case, removes square bracket, removes numbers and punctuation\n",
        "def text_clean_1(text):\n",
        "    #contraction\n",
        "    contraction = sample_contraction_replacer.do_contraction_normalization(text)\n",
        "    p = ''.join(c for c in contraction if c not in punctuation)\n",
        "    #Lower case\n",
        "    L =p.lower()\n",
        "    #tokenize\n",
        "    tokenize = nltk.word_tokenize(L)\n",
        "    #remove stop words\n",
        "    stop_w = stopwords.words('english')\n",
        "    lst = [w for w in tokenize if w not in stop_w]     \n",
        "    new_text = ' '.join(lst)  \n",
        "    return new_text\n",
        "\n",
        "cleaned1 = lambda x: text_clean_1(x)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D_r_XA-3OENQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "outputId": "a4b6f579-93fb-43ce-e339-638404a06cab"
      },
      "source": [
        "# Let's take a look at the updated text\n",
        "Reviewdata['review_clean'] = pd.DataFrame(Reviewdata.review.apply(cleaned1))\n",
        "Reviewdata.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<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>title</th>\n",
              "      <th>review</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>genre</th>\n",
              "      <th>plot</th>\n",
              "      <th>rating</th>\n",
              "      <th>review_clean</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Many people compare \"Once Upon a Time in Ameri...</td>\n",
              "      <td>helpful positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>many people compare upon time america godfathe...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>... Directors of all time. Let's start with a ...</td>\n",
              "      <td>helpful negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>directors time lets start story many years ago...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Simply the best movie ever made. Dot.Life. Lov...</td>\n",
              "      <td>unhelpful positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>simply best movie ever made dotlife love frien...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Once Upon a Time in America is Sergio Leone's ...</td>\n",
              "      <td>unhelpful negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>upon time america sergio leones epic tale live...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>The author of the novel and the director of th...</td>\n",
              "      <td>helpful positive</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>author novel director film say head yuppies dr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>This is a frightening and wildly satiric look ...</td>\n",
              "      <td>helpful negative</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>frightening wildly satiric look mentality high...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>I think this is the best adaptation of a Bret ...</td>\n",
              "      <td>unhelpful positive</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>think best adaptation bret eston elliss book m...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>This movie is sick, pointless and utterly bori...</td>\n",
              "      <td>unhelpful negative</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>movie sick pointless utterly boring message sh...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>The Notebook</td>\n",
              "      <td>In all honesty, my Dad paid me to go see the N...</td>\n",
              "      <td>helpful positive</td>\n",
              "      <td>Drama, Romance</td>\n",
              "      <td>In a nursing home, resident Duke reads a roman...</td>\n",
              "      <td>7.8</td>\n",
              "      <td>honesty dad paid go see notebook friends kept ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>The Notebook</td>\n",
              "      <td>Heartwarming, heart-wrenching, poignant, emoti...</td>\n",
              "      <td>helpful negative</td>\n",
              "      <td>Drama, Romance</td>\n",
              "      <td>In a nursing home, resident Duke reads a roman...</td>\n",
              "      <td>7.8</td>\n",
              "      <td>heartwarming heartwrenching poignant emotional...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                         title  ...                                       review_clean\n",
              "0  Once Upon a Time in America  ...  many people compare upon time america godfathe...\n",
              "1  Once Upon a Time in America  ...  directors time lets start story many years ago...\n",
              "2  Once Upon a Time in America  ...  simply best movie ever made dotlife love frien...\n",
              "3  Once Upon a Time in America  ...  upon time america sergio leones epic tale live...\n",
              "4              American Psycho  ...  author novel director film say head yuppies dr...\n",
              "5              American Psycho  ...  frightening wildly satiric look mentality high...\n",
              "6              American Psycho  ...  think best adaptation bret eston elliss book m...\n",
              "7              American Psycho  ...  movie sick pointless utterly boring message sh...\n",
              "8                 The Notebook  ...  honesty dad paid go see notebook friends kept ...\n",
              "9                 The Notebook  ...  heartwarming heartwrenching poignant emotional...\n",
              "\n",
              "[10 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JbfKEpOUOFd6"
      },
      "source": [
        "# Apply a second round of cleaning\n",
        "\n",
        "def text_clean_2(text):\n",
        "    #spellchecker\n",
        "    from autocorrect import Speller\n",
        "    tokenize = nltk.word_tokenize(text)\n",
        "\n",
        "    spell = Speller(lang='en')\n",
        "    result = [spell(x) for x in tokenize]\n",
        "    new_text = ' '.join(result) \n",
        "    return new_text\n",
        "\n",
        "cleaned2 = lambda x: text_clean_2(x)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rnpk5Bq9OGyK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 840
        },
        "outputId": "07a91a91-69c5-4128-afd7-0af3830e9a82"
      },
      "source": [
        "from wordcloud import WordCloud\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "positivedata = Reviewdata[ Reviewdata['sentiment'] == 'helpful positive']\n",
        "positivedata =positivedata['review']\n",
        "negdata = Reviewdata[ Reviewdata['sentiment'] == 'helpful negative']\n",
        "negdata= negdata['review']\n",
        "\n",
        "def wordcloud_draw(data, color = 'white'):\n",
        "    words = ' '.join(data)\n",
        "    cleaned_word = \" \".join([word for word in words.split()\n",
        "                              if(word!='movie' and word!='film')\n",
        "                            ])\n",
        "    wordcloud = WordCloud(stopwords=stopwords.words('english'),\n",
        "                      background_color=color,\n",
        "                      width=2500,\n",
        "                      height=2000\n",
        "                     ).generate(cleaned_word)\n",
        "    plt.figure(1,figsize=(10, 7))\n",
        "    plt.imshow(wordcloud)\n",
        "    plt.axis('off')\n",
        "    plt.show()\n",
        "    \n",
        "print(\"Positive words are as follows\")\n",
        "wordcloud_draw(positivedata,'white')\n",
        "print(\"Negative words are as follows\")\n",
        "wordcloud_draw(negdata, 'black')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Positive words are as follows\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Negative words are as follows\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SXq1GfDGOIgi",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "outputId": "94f51580-d77a-4b62-83ed-458ca9d3b2c1"
      },
      "source": [
        "\n",
        "Reviewdata['sentiment']=Reviewdata['sentiment'].replace(['helpful positive','unhelpful positive'], 'positive')\n",
        "Reviewdata['sentiment']=Reviewdata['sentiment'].replace(['helpful negative','unhelpful negative'], 'negative')\n",
        "\n",
        "Reviewdata.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>title</th>\n",
              "      <th>review</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>genre</th>\n",
              "      <th>plot</th>\n",
              "      <th>rating</th>\n",
              "      <th>review_clean</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Many people compare \"Once Upon a Time in Ameri...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>many people compare upon time america godfathe...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>... Directors of all time. Let's start with a ...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>directors time lets start story many years ago...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Simply the best movie ever made. Dot.Life. Lov...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>simply best movie ever made dotlife love frien...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Once Upon a Time in America is Sergio Leone's ...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>upon time america sergio leones epic tale live...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>The author of the novel and the director of th...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>author novel director film say head yuppies dr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>This is a frightening and wildly satiric look ...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>frightening wildly satiric look mentality high...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>I think this is the best adaptation of a Bret ...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>think best adaptation bret eston elliss book m...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>This movie is sick, pointless and utterly bori...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>movie sick pointless utterly boring message sh...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>The Notebook</td>\n",
              "      <td>In all honesty, my Dad paid me to go see the N...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Drama, Romance</td>\n",
              "      <td>In a nursing home, resident Duke reads a roman...</td>\n",
              "      <td>7.8</td>\n",
              "      <td>honesty dad paid go see notebook friends kept ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>The Notebook</td>\n",
              "      <td>Heartwarming, heart-wrenching, poignant, emoti...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Drama, Romance</td>\n",
              "      <td>In a nursing home, resident Duke reads a roman...</td>\n",
              "      <td>7.8</td>\n",
              "      <td>heartwarming heartwrenching poignant emotional...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                         title  ...                                       review_clean\n",
              "0  Once Upon a Time in America  ...  many people compare upon time america godfathe...\n",
              "1  Once Upon a Time in America  ...  directors time lets start story many years ago...\n",
              "2  Once Upon a Time in America  ...  simply best movie ever made dotlife love frien...\n",
              "3  Once Upon a Time in America  ...  upon time america sergio leones epic tale live...\n",
              "4              American Psycho  ...  author novel director film say head yuppies dr...\n",
              "5              American Psycho  ...  frightening wildly satiric look mentality high...\n",
              "6              American Psycho  ...  think best adaptation bret eston elliss book m...\n",
              "7              American Psycho  ...  movie sick pointless utterly boring message sh...\n",
              "8                 The Notebook  ...  honesty dad paid go see notebook friends kept ...\n",
              "9                 The Notebook  ...  heartwarming heartwrenching poignant emotional...\n",
              "\n",
              "[10 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0JSxzyu_OJCC"
      },
      "source": [
        "# Model Training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4kFBr1xzO9q6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d65629fd-c25f-4653-d5a2-6773b5137c43"
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "Independent_var = Reviewdata.review_clean\n",
        "Dependent_var = Reviewdata.sentiment\n",
        "\n",
        "IV_train, IV_test, DV_train, DV_test = train_test_split(Independent_var, Dependent_var, test_size = 0.1, random_state = 225)\n",
        "\n",
        "print('IV_train :', len(IV_train))\n",
        "print('IV_test  :', len(IV_test))\n",
        "print('DV_train :', len(DV_train))\n",
        "print('DV_test  :', len(DV_test))\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "IV_train : 3600\n",
            "IV_test  : 400\n",
            "DV_train : 3600\n",
            "DV_test  : 400\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P8GiRS3LO-q5"
      },
      "source": [
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "\n",
        "tvec = TfidfVectorizer()\n",
        "clf2 = LogisticRegression(solver = \"lbfgs\")\n",
        "\n",
        "\n",
        "from sklearn.pipeline import Pipeline"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PufxF21APBLl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3adf3b69-cb56-4258-c395-44d2903b46a8"
      },
      "source": [
        "model = Pipeline([('vectorizer',tvec),('classifier',clf2)])\n",
        "\n",
        "model.fit(IV_train, DV_train)\n",
        "\n",
        "\n",
        "from sklearn.metrics import confusion_matrix\n",
        "\n",
        "predictions = model.predict(IV_test)\n",
        "\n",
        "confusion_matrix(predictions, DV_test)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[133,  46],\n",
              "       [ 63, 158]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "moUXaom9PDNS"
      },
      "source": [
        "# Model Prediction"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4EOMd9gdPHpE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c7b4fd55-4e77-48a5-c002-e115961a2cda"
      },
      "source": [
        "from sklearn.metrics import accuracy_score, precision_score, recall_score\n",
        "\n",
        "print(\"Accuracy : \", accuracy_score(predictions, DV_test))\n",
        "print(\"Precision : \", precision_score(predictions, DV_test, average = 'weighted'))\n",
        "print(\"Recall : \", recall_score(predictions, DV_test, average = 'weighted'))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Accuracy :  0.7275\n",
            "Precision :  0.731577380952381\n",
            "Recall :  0.7275\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6plTjUfPQJAT"
      },
      "source": [
        "# Trying on New Reviews"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KqdG2Er4QH3M",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f812e46c-4ea2-48b7-df24-4b9c554cd7c6"
      },
      "source": [
        "example = [\"awesome\"]\n",
        "result = model.predict(example)\n",
        "\n",
        "print(result)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['positive']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iSV-6aMKQVz-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "31597960-b58d-45f1-965e-e72debab3f6d"
      },
      "source": [
        "#this takes almost 10 mnts to execute\n",
        "reviews =Reviewdata['review_clean']\n",
        "print(len(reviews))\n",
        "flag = 0\n",
        "positive_count=[]\n",
        "negative_count=[]\n",
        "while flag != len(reviews):\n",
        "  count = 0\n",
        "  ncount = 0\n",
        "  for word in reviews[flag].split(' '):\n",
        "    b = model.predict([word])\n",
        "    if b == 'positive':\n",
        "      count +=1\n",
        "    else:\n",
        "      ncount +=1\n",
        "  flag +=1\n",
        "  positive_count.append(count)\n",
        "  negative_count.append(ncount)\n",
        "\n",
        "Reviewdata['Positive_count'] = positive_count\n",
        "Reviewdata['Negative_count'] = negative_count\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zgcJB257QXYK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "outputId": "89f5801d-2112-4e15-b74d-b84866d6183f"
      },
      "source": [
        "Reviewdata"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>title</th>\n",
              "      <th>review</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>genre</th>\n",
              "      <th>plot</th>\n",
              "      <th>rating</th>\n",
              "      <th>review_clean</th>\n",
              "      <th>Positive_count</th>\n",
              "      <th>Negative_count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Many people compare \"Once Upon a Time in Ameri...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>many people compare upon time america godfathe...</td>\n",
              "      <td>77</td>\n",
              "      <td>162</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>... Directors of all time. Let's start with a ...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>directors time lets start story many years ago...</td>\n",
              "      <td>81</td>\n",
              "      <td>250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Simply the best movie ever made. Dot.Life. Lov...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>simply best movie ever made dotlife love frien...</td>\n",
              "      <td>28</td>\n",
              "      <td>50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Once Upon a Time in America is Sergio Leone's ...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>upon time america sergio leones epic tale live...</td>\n",
              "      <td>88</td>\n",
              "      <td>334</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>The author of the novel and the director of th...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>author novel director film say head yuppies dr...</td>\n",
              "      <td>14</td>\n",
              "      <td>36</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3995</th>\n",
              "      <td>Delicatessen</td>\n",
              "      <td>I'm going to go against what virtually everyon...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Comedy, Crime</td>\n",
              "      <td>Centered on a post-apocalyptic society where f...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>going go virtually everyone else said emperor ...</td>\n",
              "      <td>4</td>\n",
              "      <td>27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3996</th>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>I'll say one thing right off the bat, this mov...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "      <td>say one thing right bat movie incredible saw p...</td>\n",
              "      <td>26</td>\n",
              "      <td>51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3997</th>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>This movie has a message every Brazilian shoul...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "      <td>movie message every brazilian think problem br...</td>\n",
              "      <td>11</td>\n",
              "      <td>43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3998</th>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>There is something so beautiful in the craft t...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "      <td>something beautiful craft shown without violen...</td>\n",
              "      <td>35</td>\n",
              "      <td>134</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3999</th>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>*** WARNING: Some spoilers follow...Don't beli...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "      <td>warning spoilers followdont believe hype film ...</td>\n",
              "      <td>20</td>\n",
              "      <td>135</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4000 rows × 9 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                title  ... Negative_count\n",
              "0         Once Upon a Time in America  ...            162\n",
              "1         Once Upon a Time in America  ...            250\n",
              "2         Once Upon a Time in America  ...             50\n",
              "3         Once Upon a Time in America  ...            334\n",
              "4                     American Psycho  ...             36\n",
              "...                               ...  ...            ...\n",
              "3995                     Delicatessen  ...             27\n",
              "3996  Elite Squad 2: The Enemy Within  ...             51\n",
              "3997  Elite Squad 2: The Enemy Within  ...             43\n",
              "3998  Elite Squad 2: The Enemy Within  ...            134\n",
              "3999  Elite Squad 2: The Enemy Within  ...            135\n",
              "\n",
              "[4000 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bMdZebziQbI8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "outputId": "ad9c78ec-1891-40ab-9213-5dac7eabf47a"
      },
      "source": [
        "#create a column for interesting/uninteresting reviews\n",
        "import numpy as np\n",
        "\n",
        "Reviewdata['Interesting/Uninteresting'] = np.where((Reviewdata['Positive_count'] <100 ) & (Reviewdata['Negative_count'] < 100)\n",
        "                     , 'Uninteresting','Interesting')\n",
        "\n",
        "Reviewdata"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>title</th>\n",
              "      <th>review</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>genre</th>\n",
              "      <th>plot</th>\n",
              "      <th>rating</th>\n",
              "      <th>review_clean</th>\n",
              "      <th>Positive_count</th>\n",
              "      <th>Negative_count</th>\n",
              "      <th>Interesting/Uninteresting</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Many people compare \"Once Upon a Time in Ameri...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>many people compare upon time america godfathe...</td>\n",
              "      <td>77</td>\n",
              "      <td>162</td>\n",
              "      <td>Interesting</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>... Directors of all time. Let's start with a ...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>directors time lets start story many years ago...</td>\n",
              "      <td>81</td>\n",
              "      <td>250</td>\n",
              "      <td>Interesting</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Simply the best movie ever made. Dot.Life. Lov...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>simply best movie ever made dotlife love frien...</td>\n",
              "      <td>28</td>\n",
              "      <td>50</td>\n",
              "      <td>Uninteresting</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Once Upon a Time in America is Sergio Leone's ...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>upon time america sergio leones epic tale live...</td>\n",
              "      <td>88</td>\n",
              "      <td>334</td>\n",
              "      <td>Interesting</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>The author of the novel and the director of th...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>author novel director film say head yuppies dr...</td>\n",
              "      <td>14</td>\n",
              "      <td>36</td>\n",
              "      <td>Uninteresting</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3995</th>\n",
              "      <td>Delicatessen</td>\n",
              "      <td>I'm going to go against what virtually everyon...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Comedy, Crime</td>\n",
              "      <td>Centered on a post-apocalyptic society where f...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>going go virtually everyone else said emperor ...</td>\n",
              "      <td>4</td>\n",
              "      <td>27</td>\n",
              "      <td>Uninteresting</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3996</th>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>I'll say one thing right off the bat, this mov...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "      <td>say one thing right bat movie incredible saw p...</td>\n",
              "      <td>26</td>\n",
              "      <td>51</td>\n",
              "      <td>Uninteresting</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3997</th>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>This movie has a message every Brazilian shoul...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "      <td>movie message every brazilian think problem br...</td>\n",
              "      <td>11</td>\n",
              "      <td>43</td>\n",
              "      <td>Uninteresting</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3998</th>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>There is something so beautiful in the craft t...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "      <td>something beautiful craft shown without violen...</td>\n",
              "      <td>35</td>\n",
              "      <td>134</td>\n",
              "      <td>Interesting</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3999</th>\n",
              "      <td>Elite Squad 2: The Enemy Within</td>\n",
              "      <td>*** WARNING: Some spoilers follow...Don't beli...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Action, Crime, Drama, Thriller</td>\n",
              "      <td>After a bloody invasion of the BOPE in the Hig...</td>\n",
              "      <td>8.0</td>\n",
              "      <td>warning spoilers followdont believe hype film ...</td>\n",
              "      <td>20</td>\n",
              "      <td>135</td>\n",
              "      <td>Interesting</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4000 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                title  ... Interesting/Uninteresting\n",
              "0         Once Upon a Time in America  ...               Interesting\n",
              "1         Once Upon a Time in America  ...               Interesting\n",
              "2         Once Upon a Time in America  ...             Uninteresting\n",
              "3         Once Upon a Time in America  ...               Interesting\n",
              "4                     American Psycho  ...             Uninteresting\n",
              "...                               ...  ...                       ...\n",
              "3995                     Delicatessen  ...             Uninteresting\n",
              "3996  Elite Squad 2: The Enemy Within  ...             Uninteresting\n",
              "3997  Elite Squad 2: The Enemy Within  ...             Uninteresting\n",
              "3998  Elite Squad 2: The Enemy Within  ...               Interesting\n",
              "3999  Elite Squad 2: The Enemy Within  ...               Interesting\n",
              "\n",
              "[4000 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KdhSODpHQtqU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "outputId": "e8fc8a59-dacb-4f5b-a9e3-3db9d68b2c20"
      },
      "source": [
        "#interesting reviews\n",
        "# Ten largest values in column Weight\n",
        "top_positive = Reviewdata.nlargest(5, ['Positive_count'])\n",
        "top_negative = Reviewdata.nlargest(5, ['Negative_count'])\n",
        "filtereddf = pd.concat([top_positive,top_negative])\n",
        "\n",
        "#plot number of positive and negative words and corresponding movie titles on the graph\n",
        "\n",
        "filtereddf.plot(x=\"title\", y=[\"Positive_count\", \"Negative_count\"], kind=\"barh\",figsize=(10,8))\n",
        "plt.xlabel('Number of words')\n",
        "plt.ylabel('Movie title')\n",
        "plt.title('Interesting movie reviews')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Interesting movie reviews')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1an4_kmPVF13"
      },
      "source": [
        "# Finding Movie Recommendations"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oXqov-7ScFLl"
      },
      "source": [
        "#!pip install rake_nltk\n",
        "from rake_nltk import Rake\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.metrics.pairwise import cosine_similarity\n",
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "\n",
        "import re\n",
        "from string import punctuation\n",
        "from textblob import TextBlob\n",
        "from nltk import stem\n",
        "from nltk.corpus import stopwords\n",
        "import nltk\n",
        "#nltk.download('all')\n",
        "from nltk.stem import LancasterStemmer, WordNetLemmatizer, PorterStemmer"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KXhKur4jb7tH"
      },
      "source": [
        "# Based on Content"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "id": "SOMFNBB-lRUH",
        "outputId": "37fbd042-695d-4700-dff6-05a165af933e"
      },
      "source": [
        "Reviewdata.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>title</th>\n",
              "      <th>review</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>genre</th>\n",
              "      <th>plot</th>\n",
              "      <th>rating</th>\n",
              "      <th>review_clean</th>\n",
              "      <th>Positive_count</th>\n",
              "      <th>Negative_count</th>\n",
              "      <th>Interesting/Uninteresting</th>\n",
              "      <th>review_keywords</th>\n",
              "      <th>movie_keywords</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Many people compare \"Once Upon a Time in Ameri...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>many people compare upon time america godfathe...</td>\n",
              "      <td>77</td>\n",
              "      <td>162</td>\n",
              "      <td>Interesting</td>\n",
              "      <td>america, many, people, compare, upon, time, go...</td>\n",
              "      <td>guilt, even, self, worn, leather, suitcase, re...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>... Directors of all time. Let's start with a ...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>directors time lets start story many years ago...</td>\n",
              "      <td>81</td>\n",
              "      <td>250</td>\n",
              "      <td>Interesting</td>\n",
              "      <td>upon, time, america, directors, lets, start, s...</td>\n",
              "      <td>guilt, even, self, worn, leather, suitcase, re...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Simply the best movie ever made. Dot.Life. Lov...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>simply best movie ever made dotlife love frien...</td>\n",
              "      <td>28</td>\n",
              "      <td>50</td>\n",
              "      <td>Uninteresting</td>\n",
              "      <td>america, simply, best, movie, ever, made, dotl...</td>\n",
              "      <td>guilt, even, self, worn, leather, suitcase, re...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Once Upon a Time in America is Sergio Leone's ...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>upon time america sergio leones epic tale live...</td>\n",
              "      <td>88</td>\n",
              "      <td>334</td>\n",
              "      <td>Interesting</td>\n",
              "      <td>america, upon, time, sergio, leones, epic, tal...</td>\n",
              "      <td>guilt, even, self, worn, leather, suitcase, re...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>American Psycho</td>\n",
              "      <td>The author of the novel and the director of th...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Comedy, Crime, Drama</td>\n",
              "      <td>It's the late 1980s. Twenty-seven year old Wal...</td>\n",
              "      <td>7.6</td>\n",
              "      <td>author novel director film say head yuppies dr...</td>\n",
              "      <td>14</td>\n",
              "      <td>36</td>\n",
              "      <td>Uninteresting</td>\n",
              "      <td>american, psycho, author, novel, director, fil...</td>\n",
              "      <td>always, late, 1980s, others, unlike, proverbia...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                         title  ...                                     movie_keywords\n",
              "0  Once Upon a Time in America  ...  guilt, even, self, worn, leather, suitcase, re...\n",
              "1  Once Upon a Time in America  ...  guilt, even, self, worn, leather, suitcase, re...\n",
              "2  Once Upon a Time in America  ...  guilt, even, self, worn, leather, suitcase, re...\n",
              "3  Once Upon a Time in America  ...  guilt, even, self, worn, leather, suitcase, re...\n",
              "4              American Psycho  ...  always, late, 1980s, others, unlike, proverbia...\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 176
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "inERGSqWdugb"
      },
      "source": [
        "Reviewdata['movie_keywords'] = ''\n",
        "r = Rake()\n",
        "for index, row in Reviewdata.iterrows():\n",
        "    r.extract_keywords_from_text(row['title'] + ' ' + row['genre'] + ' ' + row['plot'])\n",
        "    key_words_dict_scores = r.get_word_degrees()\n",
        "\n",
        "    Reviewdata.at[index, 'movie_keywords'] = ', '.join(list(key_words_dict_scores.keys())) + ' ' + row['genre'] + ', ' + row['title']\n",
        "    #Reviewdata.at[index, 'movie_keywords'] = 'asasfasdf'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3qKSCh85lK2Q"
      },
      "source": [
        "# Gets recommendations based on how well passed search text matches movie data\n",
        "def get_recs(search_string, title=''):\n",
        "  count = CountVectorizer()\n",
        "  count_matrix = count.fit_transform(Reviewdata['movie_keywords'])\n",
        "  cosine_sim = cosine_similarity(count_matrix, count_matrix)\n",
        "\n",
        "  recommendations = {}\n",
        "  \n",
        "  idx = Reviewdata.index[Reviewdata['title'] == title][0]\n",
        "  #print(idx)\n",
        "\n",
        "  #idx = indices[indices == title].index[0] \n",
        "  score_series = pd.Series(cosine_sim[idx]).sort_values(ascending = False)\n",
        "  #print(score_series)\n",
        "  top_10_indices = list(score_series.iloc[1:11].index)\n",
        "    # Returns the top 10 best matches in order of how closely they match \n",
        "  #print('test')\n",
        "  for i in top_10_indices:\n",
        "    #rec_title = Reviewdata['title']\n",
        "    recommendations[Reviewdata['title'][i]] = Reviewdata['rating'][i]\n",
        "  \n",
        "  return(recommendations)\n",
        "\n",
        "def recommend_by_movie_data(title):\n",
        "  #print(title)\n",
        "  #print(Reviewdata.loc[Reviewdata['title'] == title])\n",
        "  search_string = Reviewdata['movie_keywords']\n",
        "  #print(search_string)\n",
        "  recs = get_recs(search_string, title)\n",
        "  return(recs)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m1VR_r_9mljZ",
        "outputId": "8719ad10-6e25-412e-adaa-5c400fbbe6c2"
      },
      "source": [
        "model1_recs = recommend_by_movie_data('Once Upon a Time in America')\n",
        "model1_recs"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{\"Dead Man's Shoes\": 7.6,\n",
              " 'Once Upon a Time in America': 8.4,\n",
              " 'Once Upon a Time in Anatolia': 7.9}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 277
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v5DFceKycAHG"
      },
      "source": [
        "# Based on Reviews"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "id": "upwyw-AYcUFW",
        "outputId": "ad5dbd09-228b-45cb-a6ae-fc11394ab637"
      },
      "source": [
        "interesting_df = Reviewdata.loc[ Reviewdata['Interesting/Uninteresting'] == 'Interesting'] # removing \"unhelpful\" reviews so they don't inform search results\n",
        "interesting_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>title</th>\n",
              "      <th>review</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>genre</th>\n",
              "      <th>plot</th>\n",
              "      <th>rating</th>\n",
              "      <th>review_clean</th>\n",
              "      <th>Positive_count</th>\n",
              "      <th>Negative_count</th>\n",
              "      <th>Interesting/Uninteresting</th>\n",
              "      <th>review_keywords</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Many people compare \"Once Upon a Time in Ameri...</td>\n",
              "      <td>positive</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>many people compare upon time america godfathe...</td>\n",
              "      <td>77</td>\n",
              "      <td>162</td>\n",
              "      <td>Interesting</td>\n",
              "      <td>america, many, people, compare, upon, time, go...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>... Directors of all time. Let's start with a ...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>directors time lets start story many years ago...</td>\n",
              "      <td>81</td>\n",
              "      <td>250</td>\n",
              "      <td>Interesting</td>\n",
              "      <td>upon, time, america, directors, lets, start, s...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Once Upon a Time in America</td>\n",
              "      <td>Once Upon a Time in America is Sergio Leone's ...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Crime, Drama</td>\n",
              "      <td>With the vivid memory of his long-gone childho...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>upon time america sergio leones epic tale live...</td>\n",
              "      <td>88</td>\n",
              "      <td>334</td>\n",
              "      <td>Interesting</td>\n",
              "      <td>america, upon, time, sergio, leones, epic, tal...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>The Notebook</td>\n",
              "      <td>Heartwarming, heart-wrenching, poignant, emoti...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Drama, Romance</td>\n",
              "      <td>In a nursing home, resident Duke reads a roman...</td>\n",
              "      <td>7.8</td>\n",
              "      <td>heartwarming heartwrenching poignant emotional...</td>\n",
              "      <td>91</td>\n",
              "      <td>369</td>\n",
              "      <td>Interesting</td>\n",
              "      <td>notebook, heartwarming, heartwrenching, poigna...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>The Notebook</td>\n",
              "      <td>I like Rachel McAdams and Joan Allen. They act...</td>\n",
              "      <td>negative</td>\n",
              "      <td>Drama, Romance</td>\n",
              "      <td>In a nursing home, resident Duke reads a roman...</td>\n",
              "      <td>7.8</td>\n",
              "      <td>like rachel mcadams joan allen acted well coul...</td>\n",
              "      <td>27</td>\n",
              "      <td>143</td>\n",
              "      <td>Interesting</td>\n",
              "      <td>notebook, like, rachel, mcadams, joan, allen, ...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                          title  ...                                    review_keywords\n",
              "0   Once Upon a Time in America  ...  america, many, people, compare, upon, time, go...\n",
              "1   Once Upon a Time in America  ...  upon, time, america, directors, lets, start, s...\n",
              "3   Once Upon a Time in America  ...  america, upon, time, sergio, leones, epic, tal...\n",
              "9                  The Notebook  ...  notebook, heartwarming, heartwrenching, poigna...\n",
              "11                 The Notebook  ...  notebook, like, rachel, mcadams, joan, allen, ...\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PfQkW49FcM9F"
      },
      "source": [
        "Reviewdata['review_keywords'] = ''\n",
        "r = Rake()\n",
        "for index, row in Reviewdata.iterrows():\n",
        "    r.extract_keywords_from_text(row['title'] + ' ' + row['review_clean'])\n",
        "    key_words_dict_scores = r.get_word_degrees()\n",
        "\n",
        "    Reviewdata.at[index, 'review_keywords'] = ', '.join(list(key_words_dict_scores.keys()))\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vqrILXHCcXad",
        "outputId": "30bd8b08-e27e-492d-d327-8b25a8408a9a"
      },
      "source": [
        "count = CountVectorizer()\n",
        "count_matrix = count.fit_transform(interesting_df['review_keywords'])\n",
        "cosine_sim = cosine_similarity(count_matrix, count_matrix)\n",
        "print(cosine_sim)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[1.         0.23036972 0.19354735 ... 0.12716702 0.11233673 0.05973378]\n",
            " [0.23036972 1.         0.16677507 ... 0.09248166 0.09258924 0.03829255]\n",
            " [0.19354735 0.16677507 1.         ... 0.09006062 0.09944712 0.0423039 ]\n",
            " ...\n",
            " [0.12716702 0.09248166 0.09006062 ... 1.         0.0591904  0.03996676]\n",
            " [0.11233673 0.09258924 0.09944712 ... 0.0591904  1.         0.07502486]\n",
            " [0.05973378 0.03829255 0.0423039  ... 0.03996676 0.07502486 1.        ]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UBQ4hr7renWm"
      },
      "source": [
        "# Gets recommendations based on how well passed search text matches existing helpful reviews\n",
        "def get_recs(search_string, title=''):\n",
        "\n",
        "  rec_df = interesting_df.drop(interesting_df[interesting_df['title'] == title].index) # drops the movie currentnly being searched for to avoid movies recommending themselves\n",
        "  new_row = {'title': title, 'review':search_string, 'Interesting/Uninteresting':'Interesting', 'review_keywords': search_string} # creates \n",
        "\n",
        "  rec_df = rec_df.append(new_row, ignore_index = True)\n",
        "\n",
        "  count = CountVectorizer()\n",
        "  count_matrix = count.fit_transform(rec_df['review_keywords'])\n",
        "  cosine_sim = cosine_similarity(count_matrix, count_matrix)\n",
        "\n",
        "  pos_movies = []\n",
        "  neg_movies = []\n",
        "  idx = rec_df.index[rec_df['title'] == title][0]\n",
        "\n",
        "\n",
        "  #idx = indices[indices == title].index[0] \n",
        "  score_series = pd.Series(cosine_sim[idx]).sort_values(ascending = False)\n",
        "  top_10_indices = list(score_series.iloc[1:11].index)\n",
        "    # Returns the top 10 best matches in order of how closely they match \n",
        "  for i in top_10_indices:\n",
        "    if (Reviewdata['sentiment'])[i] == 'positive':\n",
        "      pos_movies.append(Reviewdata['title'][i])\n",
        "    else:\n",
        "      neg_movies.append(Reviewdata['title'][i])\n",
        "    \n",
        "  pos_movies = set(pos_movies)\n",
        "  neg_movies = set(neg_movies)\n",
        "\n",
        "  print('Movies with good reviews matching your interests:' )\n",
        "  print(pos_movies) \n",
        "  print('Movies with mixed reviews matching your interests: ' )\n",
        "  print(neg_movies)\n",
        "\n",
        "  return([pos_movies, neg_movies])\n",
        "\n",
        "def recommend_by_movie(title):\n",
        "  #print(interesting_df.loc[interesting_df['title'] == title]['review_keywords'].sum())\n",
        "  search_string = interesting_df.loc[interesting_df['title'] == title]['review_keywords'].sum() + title\n",
        "  recs = get_recs(search_string, title)\n",
        "  return recs"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W8-_pLHMg2PB",
        "outputId": "94a59950-34eb-43b2-a6d2-68ce1774d9cb"
      },
      "source": [
        "get_recs('that one movie where the iguana wearing clown shoes learns to kickbox')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Movies with good reviews matching your interests:\n",
            "{'Deliverance', 'Mulan', 'Patton', 'Donnie Brasco'}\n",
            "Movies with mixed reviews matching your interests: \n",
            "{'The Fault in Our Stars', 'The Sixth Sense', 'Fantastic Mr. Fox', 'The Gentlemen', 'Jaws', 'American Psycho'}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1jg5zuxLepD1",
        "outputId": "7c25defc-0410-45f8-8c92-6956b1c313b2"
      },
      "source": [
        "recs = recommend_by_movie('Once Upon a Time in America')\n",
        "good_fits = recs[0]\n",
        "iffy_fits = recs[1]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Movies with good reviews matching your interests:\n",
            "{'Zodiac', 'Wind River', 'Battle Royale', 'Fantastic Mr. Fox', 'Toy Story 3'}\n",
            "Movies with mixed reviews matching your interests: \n",
            "{'Memento', 'Portrait of a Lady on Fire', 'Mulan', 'Manchester by the Sea', 'Whiplash'}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "csPC1H4txARs"
      },
      "source": [
        "# Model Comparison"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xiP3k3NgxFp5",
        "outputId": "72b64c9d-3ea8-4725-ec2a-afa5c3d1f5f7"
      },
      "source": [
        "# Results from searching for movie data\n",
        "dict(sorted(model1_recs.items(), key=lambda item: item[1]))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{\"Dead Man's Shoes\": 7.6,\n",
              " 'Once Upon a Time in America': 8.4,\n",
              " 'Once Upon a Time in Anatolia': 7.9}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 278
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zSrjeIMlxRU3",
        "outputId": "f4413d00-ed3b-4e8b-98c3-4ed6643d3413"
      },
      "source": [
        "# Results from searching for reviews\n",
        "good_fits.union(iffy_fits)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Battle Royale',\n",
              " 'Fantastic Mr. Fox',\n",
              " 'Manchester by the Sea',\n",
              " 'Memento',\n",
              " 'Mulan',\n",
              " 'Portrait of a Lady on Fire',\n",
              " 'Toy Story 3',\n",
              " 'Whiplash',\n",
              " 'Wind River',\n",
              " 'Zodiac'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 279
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 191
        },
        "id": "kEM90DwG23-r",
        "outputId": "dae0ff38-e326-4ec9-de9c-3bd6252692fc"
      },
      "source": [
        "texts = ['\"I want a movie about lemurs!\"', 'this movie is about explosions', 'this one is about romance', 'this one has romantic explosions', 'this movie is about exploding lemurs']\n",
        "\n",
        "\n",
        "df = pd.DataFrame({'texts': texts})\n",
        "df\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>texts</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>\"I want a movie about lemurs!\"</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>this movie is about explosions</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>this one is about romance</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>this one has romantic explosions</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>this movie is about exploding lemurs</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                  texts\n",
              "0        \"I want a movie about lemurs!\"\n",
              "1        this movie is about explosions\n",
              "2             this one is about romance\n",
              "3      this one has romantic explosions\n",
              "4  this movie is about exploding lemurs"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 307
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rq7BMkui3cCU",
        "outputId": "7ecdac52-6c22-42fb-fd57-f02224a8d6f7"
      },
      "source": [
        "count = CountVectorizer()\n",
        "count_matrix = count.fit_transform(df['texts'])\n",
        "cosine_sim = cosine_similarity(count_matrix, count_matrix)\n",
        "print(cosine_sim)\n",
        "print(count_matrix)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[1.         0.4472136  0.2236068  0.         0.61237244]\n",
            " [0.4472136  1.         0.6        0.4        0.73029674]\n",
            " [0.2236068  0.6        1.         0.4        0.54772256]\n",
            " [0.         0.4        0.4        1.         0.18257419]\n",
            " [0.61237244 0.73029674 0.54772256 0.18257419 1.        ]]\n",
            "  (0, 0)\t1\n",
            "  (0, 5)\t1\n",
            "  (0, 6)\t1\n",
            "  (0, 11)\t1\n",
            "  (1, 0)\t1\n",
            "  (1, 2)\t1\n",
            "  (1, 4)\t1\n",
            "  (1, 6)\t1\n",
            "  (1, 10)\t1\n",
            "  (2, 0)\t1\n",
            "  (2, 4)\t1\n",
            "  (2, 7)\t1\n",
            "  (2, 8)\t1\n",
            "  (2, 10)\t1\n",
            "  (3, 2)\t1\n",
            "  (3, 3)\t1\n",
            "  (3, 7)\t1\n",
            "  (3, 9)\t1\n",
            "  (3, 10)\t1\n",
            "  (4, 0)\t1\n",
            "  (4, 1)\t1\n",
            "  (4, 4)\t1\n",
            "  (4, 5)\t1\n",
            "  (4, 6)\t1\n",
            "  (4, 10)\t1\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}