With the advancement in internet and web technology, and accessibility to electronic gadgets, the web has become widely accessible to a large user base. The internet is a massive pool of information and a platform for exchange of data. Social Networking sites are the frontrunners in enabling people share thoughts and opinions. The last decade has seen exponential rise in the number of active users of social media. This has led to abundance of open digital data with immense potential. It has opened new avenues in research of data analytics i.e., Sentiment Analysis. Sentiment Analysis is an amalgamation of machine learning and Natural Language Processing. It is used to extract, recognize and describe the view and opinion of the user on a particular topic. The sentiment can be positive or negative. Twitter is the most popular platform for social media analysis due to its well documented and free API's. This paper presents an evaluation of user sentiments on the Goods and Services Tax (GST) Bill. Copyright © 2019 American Scientific Publishers All rights reserved.