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Sentiment Classification using Word Sense Disambiguation, Senti Word Net and word occurance statistics using movie review corpus

Project description

Sentiment Classification using WSD


Sentiment Classifier using Word Sense Disambiguation using wordnet and word occurance statistics from movie review corpus nltk. Classifies into positive and negative categories.

Online Demo


In Version 0.5 all the following requirements are installed automatically. In case of troubles install those manually.

How to Install

Shell command

python install


Script Usage

Shell Commands:

senti_classifier -c file/with/review.txt

Python Usage

Shell Commands

cd sentiment_classifier/src/senti_classifier/
python -c reviews.txt

Library Usage

from senti_classifier import senti_classifier
sentences = ['The movie was the worst movie', 'It was the worst acting by the actors']
pos_score, neg_score = senti_classifier.polarity_scores(sentences)
print pos_score, neg_score
... 0.0 1.75
from senti_classifier.senti_classifier import synsets_scores
print synsets_scores['peaceful.a.01']['pos']

... 0.25


  • 0.6 Bug Fixed upon nltk upgrade

  • 0.5 No additional data required trained data is loaded automatically. Much faster/Optimized than previous versions.

  • 0.4 Added Bag of Words as a Feature as occurance statistics

  • 0.3 Sentiment Classifier First app, Using WSD module

Project details

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Source Distribution

sentiment_classifier-0.7.tar.gz (8.3 kB view hashes)

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