Twitter Sentiment Analysis on Demonetization tweets in India Using R language
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Abstract
In this global village, social media takes the front row in interacting with people. Twitter, the ninth largest social networking website in the world, is popular for its microblogging feature that allows users to share information through short messages of up to 140 characters, called tweets. It provides a platform for registered users to search for the latest news on topics of interest. With millions of tweets shared daily in real-time by its members, Twitter boasts more than 328 million active users per month. As a result, it has become a valuable source for sentiment and opinion analysis on product reviews, movie reviews, and current global issues. This paper presents sentiment analysis on the current Twitter trends, such as Demonetization, where individuals from India and around the world are sharing their opinions on various news topics in the country. Sentiment analysis involves extracting positive and negative opinions from the Twitter dataset. R Studio is utilized as the optimal environment for conducting Twitter sentiment analysis. The data is accessed from the Twitter API and written into text files as the input dataset. The sentiment analysis process begins with data cleaning, where stop words are removed from the dataset. The tweets are then classified as positive or negative based on the polarity of the words used. To visualize the results, word clouds are generated to highlight the most frequent positive and negative words. By comparing the positive and negative scores, researchers can gauge the current public pulse and opinion on the specific topics being analyzed.
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