Sentiment Classification for Social Media Posts using Machine Learning

Abstract

With the advent of online technology and its growth, the web now contains a massive amount of data for internet users, as well as a large amount of data being generated. The internet has evolved into a platform for online learning, idea exchange, and opinion sharing. People use social networking sites like Twitter, Facebook, and Google+ to share and express their opinions on a variety of topics, participate in discussions with diverse communities, and send messages all over the world. The field of sentiment analysis of twitter data has seen a lot of progress. This study focuses on Twitter sentiment analysis, which is useful for analysing information in tweets where opinions are highly structured, varied, and either positive or negative. The proposed system is build using Support Vector Machine and Random Forest Techniques