Twitter Sentiment Analysis using Na¨ive Bayes Classifier with Mutual Information Feature Selection

Sentiment analysis is an identification technique of emotion expressed in texts. The sentiment analysis goal is to determine a negative or positive opinion within a sentence or a document. Twitter is one of social medias to convey an opinion. The twitter allows its users to write opinions related to a specific topic in a tweet. The twitter data used in this research was downloaded using the twitter Application Programming Interface (API). It consisted 500 tweets about Lombok tourism that contained #lombok and #woderfullombok hashtags. The features extracted from the twitter data were selected using the Mutual Information (MI) method then they were analyzed using the Naive Bayes Classifier (NBC) model. The evaluation of sentiment analysis on the Lombok tourism twitter data in a 10-folds cross validation resulted 97.9% accuracy. Key words : Sentiment Analysis, Twitter, Naive Bayes Classifier, Mutual Information.