Twitter Sentiment Analysis using Na¨ive Bayes Classifier with Mutual Information Feature Selection - Maria Arista Ulfa; Budi Irmawati; Ario Yudo Husodo (Informatics Engineering Dept., Faculty of Engineering, University of Mataram, 2018)
Sentiment analysis is an identification technique of emotion expressed in texts. Thesentiment analysis goal is to determine a negative or positive opinion within a sentenceor a document. Twitter is one of social medias to convey an opinion. The twitter allowsits users to write opinions related to a specific topic in a tweet. The twitter data used inthis 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 selectedusing the Mutual Information (MI) method then they were analyzed using the NaïveBayes Classifier (NBC) model. The evaluation of sentiment analysis on the Lomboktourism twitter data in a 10-folds cross validation resulted 97.9% accuracy.Key words : Sentiment Analysis, Twitter, Naïve Bayes Classifier, Mutual Information.