Fast and accurate sentiment classification using an enhanced Naive Bayes model
2013-05-27Code Available0· sign in to hype
Vivek Narayanan, Ishan Arora, Arjun Bhatia
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- github.com/vivekn/sentimentOfficialIn papernone★ 0
- github.com/memesteraati/Test-Sentiment-Analysis-tool-for-long-textsnone★ 0
- github.com/Weisewill/InsightHonestReviewnone★ 0
Abstract
We have explored different methods of improving the accuracy of a Naive Bayes classifier for sentiment analysis. We observed that a combination of methods like negation handling, word n-grams and feature selection by mutual information results in a significant improvement in accuracy. This implies that a highly accurate and fast sentiment classifier can be built using a simple Naive Bayes model that has linear training and testing time complexities. We achieved an accuracy of 88.80% on the popular IMDB movie reviews dataset.