REVIEW ON SENTIMENT ANALYSIS OF TWITTER DATA USING DIFFERENT TECHNIQUES

Abstract

Sentiment analysis in Twitter tackles the issue of investigating the tweets regarding the opinion they express. This survey centers chiefly around sentiment analysis of twitter information which is useful to investigate the data in the tweets where opinions are profoundly unstructured, heterogeneous and are either sure or negative, or unbiased now and again. In this paper, we give an audit and relative investigations of existing techniques like machine learning, profound learning and Hybrid strategy. Utilizing different machine learning algorithms like Naive Bayes, lexicon-based, and Support Vector Machine, we give research on twitter information streams. We have additionally examined merits and bad marks of existing techniques of Sentiment Analysis on Twitter.