sentiment_classifier 0.7

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

Sentiment Classification using WSD

• pip install sentiment_classifier

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Overview

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

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Requirements

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

• You must have Python 2.6.

• NLTK http://www.nltk.org 2.0 installed.

• NumPy http://numpy.scipy.org

• SentiWordNet http://sentiwordnet.isti.cnr.it

How to Install

Shell command

python setup.py install

Documentation

• http://pythonhosted.org/sentiment_classifier/

Script Usage

Shell Commands:

senti_classifier -c file/with/review.txt

Python Usage

Shell Commands

cd sentiment_classifier/src/senti_classifier/
python senti_classifier.py -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

History

• 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