No abstract

Online forums and social networking websites provide users with a platform for expressing their opinions. Manually evaluating these reviews for crucial analytical information is cumbersome. Sentiment analysis deals with analyzing such massively available textual data and determining its polarity. This research paper provides a comparative study of multiple well-known supervised machine learning algorithms on three standard datasets confined to the domain of movie reviews. The study is supported by illustrative plots and experimental results. The research work can be used as a base for further exploration in predicting the sentiment value of textual data in alternate domains using advanced machine learning algorithms.