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To classify the sentiment of sentences from the Rotten Tomatoes dataset. Labeled phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive and then predict the overall sentiment of the sentence using Naiive Bayes and Decision Tree Algorithms

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Movie-Review-Sentiment-Analysis

To classify the sentiment of sentences from the Rotten Tomatoes dataset. Labeled phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive and then predict the overall sentiment of the sentence using Naiive Bayes and Decision Tree Algorithms

How does sentiment Analysis work?

Basic sentiment analysis of text documents follows a straightforward process:

  • Break each text document down into its component parts (sentences, phrases, tokens and parts of speech)
  • Identify each sentiment-bearing phrase and component
  • Assign a sentiment score to each phrase and component (-1 to +1)
  • Optional: Combine scores for multi-layered sentiment analysis

Sentiment-Analysis-On-Movie-Reviews

Sentiment analysis on Rotten Tomatoes Dataset

The dataset is taken from kaggle https://www.kaggle.com/c/sentiment-analysis-on-movie-reviews

Algorithms used:

  1. Naive Bayes
  2. Decision Tree

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To classify the sentiment of sentences from the Rotten Tomatoes dataset. Labeled phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive and then predict the overall sentiment of the sentence using Naiive Bayes and Decision Tree Algorithms

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