Sense GST: Text mining & sentiment analysis of GST tweets by Naive Bayes algorithm

In this modern era of communication, people are always connected to the internet. Hence, everyone tends to express their opinions on social media or e-commerce websites about commercial products, movies, sports, social and geopolitical matters and even on government policies. These opinions reflect the corresponding person's view or sentiment about that particular matter, which ultimately leads to the formation of opinion polarity regarding a specific issue. In today's context, Twitter, Facebook or other social platforms often witness a lot of opinion waves regarding some of the today's most hot topics, and one of them surely is the introduction of Goods and Services Tax or GST in India. The rising sentiment analysis and opinion mining regarding this issue is helping researchers to understand the insight of public emotion. It can be also implemented to gain an idea of allover opinion polarity of people in this matter. GST was one of the most rending topic on social network platforms during Jun-July 2017, so in this paper, we present a simple and robust work to gather, analyze and graphically represent people's opinion about India's new taxation system using Naive Bayes algorithm.