Paper Title
Sentiment Analysis Of Product Reviews For E-Commerce Recommendation

The social web has made enormous amounts of information available to users globally at just the click of a button. Consumers often tend to rely on such text, especially those in the form of opinions or experiences regarding a particular product which makes it essential that this information should be available in a systematic manner. Sentiment analysis studies these opinions. This paper explains different methods for sentiment analysis and showcases an efficient methodology. It also highlights the importance of Naïve Bayes classifier over other classification algorithms. Keywords— Sentiment analysis, E-commerce, Machine learning, NaïveBayes, WordNet.