Author : Shreyas Borwankar and Dr. Mininath Nighot

Development of web technology and its growth lead to a large volume of data present in the world wide web for users, also a lot of data is generated via sites present on the web. The Internet has become a platform for various things such as online learning, social networking, exchanging ideas, online marketing and sharing opinions. Social networking sites like Facebook, Google+, Twitter are rapidly becoming popular as they allow people to express their views about different topics, have a discussion within communities, independent of the location post messages across the world. Natural language processing, sentiment analysis these are continuously evolving fields, there is a vast scope of development in these fields. Sentiment analysis of Twitter data is mainly focused in this paper. On Twitter, information is present in form of tweets where opinions are heterogeneous, highly unstructured and are either negative or positive, or neutral in some cases. Various machine learning algorithms are used for sentiment analysis of tweets and their comparison is carried out in this paper.

Keywords: Twitter, Sentiment Analysis, Machine Learning