Fast and accurate sentiment classification using an enhanced Naive Bayes model

Vivek Narayanan; Ishan Arora; Arjun Bhatia

doi:10.1007/978-3-642-41278-3_24

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arXiv · 1305.6143

Fast and accurate sentiment classification using an enhanced Naive Bayes model

Vivek Narayanan·Ishan Arora·Arjun Bhatia

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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.

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Vivek Narayanan, Ishan Arora, Arjun Bhatia. 2013-09-16. Fast and accurate sentiment classification using an enhanced Naive Bayes model. https://doi.org/10.1007/978-3-642-41278-3_24

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