Sentiment Analysis Using Naïve Bayes

In the paper “Thumbs up? Sentiment Classification using Machine Learning Techniques.”, Pang et al introduced the idea of sentiment analysis using a Naïve Bayes classifier. The key idea is to combine the probability of occurrence of the words in positive and negative sentiment reviews, probability of occurrence of the words across all reviews, probability of occurrence of positive or negative reviews across all reviews to determine the probability of a text being a positive or negative based on the words in the text.