Sentiment Analysis of Twitter for Election Prediction
Balika J. Chellia1, Kartikaya Srivastava2, Jishnu Panja3, Ritwik Paul4
1Balika J. Chellia*, Department of Computer Science and Engineering ,SRM Institute of Science and Technology, Ramapuram, Chennai, India.
2Kartikaya Srivastava, Department of Computer Science and Engineering ,SRM Institute of Science and Technology, Ramapuram, Chennai, India.
3Jishnu Panja, Department of Computer Science and Engineering ,SRM Institute of Science and Technology, Ramapuram, Chennai, India.
4Ritwik Paul, Department of Computer Science and Engineering ,SRM Institute of Science and Technology, Ramapuram, Chennai, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on October 05, 2019. | Manuscript published on October 30, 2019. | PP: 6187-6192 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1767109119/2019©BEIESP | DOI: 10.35940/ijeat.A1767.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Elections are considered to be the most important feature of a democracy. In the past few years, election analysis and predictions have become very important for political parties and news organizations. The influx of various social media platforms such as twitter, Facebook and YouTube have drawn a large number of people that share their ideological and political thoughts and hence, it’s become important to analyse them in a much more sophisticated manner. Various data mining algorithms have been used to extract tweets and perform sentiment analysis pertaining to a related topic. Sentiment analysis refers to the technique to identify positive, negative or neutral opinions from a text. Though the use of sentiment analysis we will analyse the sentiment score for the two main political parties of India. The paper will brief on various techniques that have been used for election predictions. Various results from different methods have been included in this paper along with precision, accuracy and validity of the final outcome. The main aim of this paper is to create a model for the better prediction that will help in the analysis of voting choices of users. To increase the validity of the final results, various refining techniques have been used so that only relevant tweets are analysed.
Keywords: Data mining, Election prediction, Sentiment analysis, Twitter.