Sentiment analysis is a process of finding polarity of the sentence and classify the sentence or document as positive and negative. There is a vast amount of data generated in social media in the form of blogs, comments, product reviews, tweets, status, etc. Sentiment analysis in Twitter has become a good research topic in recent years. As Twitter allows only 140 characters, it is very challenging to determine whether the tweet was a positive or negative tweet. There are many algorithms to analyse the polarity of the sentence. After studying major sentiment analysis algorithms, we evaluate the performance of these algorithms.
Sentiment Analysis, Naïve Bayes, Support Vector Machine, Maximum Entropy Classifier, Ensemble Classifier.