• Shwetha bm
• Dr.H Venugopal

Sentiment analysis is considered to be a category of machine learning and natural language processing. It is used to extricate, recognize, or portray opinions from different content structures, including news, audits and articles and categorizes them as positive, neutral and negative. It is difficult to predict election results from tweets in different Indian languages. We used Twitter Archiver tool to get tweets in language. We performed data (text) mining on tweets collected over a period of a time that referenced three national political parties in India, during the campaigning period for general state elections in 2019. We made use of both supervised and unsupervised approaches. We utilized Dictionary Based, Naive Bayes algorithm to build our classifier and classified the test data as positive, negative and neutral. We identified the sentiment of Twitter users towards each of the considered Indian political parties.

Sentiment Analysis; Twitter; Indian Elections; Naive Bayes;

"Twitter based prediction and analysis of election", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.540-544, May-2019, Available :http://www.jetir.org/papers/JETIR1905Q75.pdf

"Twitter based prediction and analysis of election", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp540-544, May-2019, Available at : http://www.jetir.org/papers/JETIR1905Q75.pdf