Sentiment Analysis on Good Service Tax (GST) using Twitter Data

Abstract

The social media has increased the opportunity to explore and track the response of new reforms and policies in India. Social Media helps in the analysis of stock market data, new product launch and movie release. One of the social networking websites is Twitter and it is the ninth largest website. 

With Twitter, the registered users can search for the latest information on the topics of their interest.  Since lakhs of tweets are shared on a real-time basis by the members every day, it has got more than 328 million active users a month. Twitter is the best source for the analysis of opinion and sentiment on movie reviews, product reviews and current issues in the world. Twitter is used widely as a forum for understanding the sentiments of Indians towards recently launched Goods and Services Tax by the Indian Government on 1st July 2017.

Sentiment analysis extracts positive and negative opinions from the twitter dataset and R Studio provides the best environment for this Twitter sentiment analysis. Data is written into text files as the input dataset so that Twitter data could be accessed from Twitter API. Sentiment analysis is performed on the input dataset that initially performs data cleaning by removing the stop words and then by classifying the tweets as positive and negative by considering the polarity of words. Finally, positive, negative and neutral is generated, comparing the polarity of the tweets