4.2 Rule Based Sentiment.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4.2 Rule-based Sentiment Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Textblob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from textblob import TextBlob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence_1 = \"i had a great time at the movie it was really funny\"\n",
    "sentence_2 = \"i had a great time at the movie but the parking was terrible\"\n",
    "sentence_3 = \"i had a great time at the movie but the parking wasn't great\"\n",
    "sentence_4 = \"i went to see a movie\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i had a great time at the movie it was really funny\n",
      "0.525\n"
     ]
    }
   ],
   "source": [
    "print(sentence_1)\n",
    "sentiment_score = TextBlob(sentence_1)\n",
    "print(sentiment_score.sentiment.polarity)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TextBlob returns a score between -1 and 1, where negative scores indicate negative sentiment, and positive scores indicate positive sentiment. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i had a great time at the movie but the parking was terrible\n",
      "-0.09999999999999998\n"
     ]
    }
   ],
   "source": [
    "print(sentence_2)\n",
    "sentiment_score_2 = TextBlob(sentence_2)\n",
    "print(sentiment_score_2.sentiment.polarity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i had a great time at the movie but the parking wasn't great\n",
      "0.8\n"
     ]
    }
   ],
   "source": [
    "print(sentence_3)\n",
    "sentiment_score_3 = TextBlob(sentence_3)\n",
    "print(sentiment_score_3.sentiment.polarity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i went to see a movie\n",
      "0.0\n"
     ]
    }
   ],
   "source": [
    "print(sentence_4)\n",
    "sentiment_score_4 = TextBlob(sentence_4)\n",
    "print(sentiment_score_4.sentiment.polarity)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### VADER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "vader_sentiment = SentimentIntensityAnalyzer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i had a great time at the movie it was really funny\n",
      "{'neg': 0.0, 'neu': 0.578, 'pos': 0.422, 'compound': 0.807}\n"
     ]
    }
   ],
   "source": [
    "print(sentence_1)\n",
    "print(vader_sentiment.polarity_scores(sentence_1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The compond score gives us the overall score for the text and is scored the same as TextBlob between -1 and 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i had a great time at the movie but the parking was terrible\n",
      "{'neg': 0.234, 'neu': 0.621, 'pos': 0.144, 'compound': -0.3818}\n"
     ]
    }
   ],
   "source": [
    "print(sentence_2)\n",
    "print(vader_sentiment.polarity_scores(sentence_2)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i had a great time at the movie but the parking wasn't great\n",
      "{'neg': 0.247, 'neu': 0.611, 'pos': 0.142, 'compound': -0.4387}\n"
     ]
    }
   ],
   "source": [
    "print(sentence_3)\n",
    "print(vader_sentiment.polarity_scores(sentence_3)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i went to see a movie\n",
      "{'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0}\n"
     ]
    }
   ],
   "source": [
    "print(sentence_4)\n",
    "print(vader_sentiment.polarity_scores(sentence_4)) "
   ]
  }
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