A simple dictionary-based tool for sentiment scoring a sentence based on SentiWordNet 3.0
Sentiment scores are between -1 and 1, greater than 0 for positive and less than 0 for negative.
Dictionary-based sentiment analysis does not perform as well as a trained classifier, but it is domain-independent, based on a priori knowledge of words' sentiment values.
The class handles negations and multiword expressions.
nltk including tokenizers
First download SentiWordNet 3.0 here, and delete any header and footer lines so that the file contains only data, e.g.
a 00001740 0.125 0 able#1 (usually followed by 'to') having the necessary...
Initialize SentimentAnalysis with your SentiWordNet filesname and choice of weighting across word senses.
s = SentimentAnalysis(filename='SentiWordNet.txt',weighting='geometric')
>>> s.score('I love you!')
0.59375
>>> s.score('Pants are the worst.')
-0.125
>>> s.score('I do not particularly enjoy this product.')
-0.15885416666666666The weighting can be 'average', 'geometric' or 'harmonic'. See Guerini et al. "Sentiment Analysis: How to Derive Prior Polarities from SentiWordNet".