A Systematic Review of Predicting Elections Based on Social Media Data

A Systematic Review of Predicting Elections Based on Social  Media Data

1 Nayana H M, 2Roopa R

1Sem MCA Student, Department of MCA, BIET, Davanagere

2Assistant Professor, Department of MCA, BIET, Davanagere

Abstract - Elections in India has always been considered as an important event and has been keenly followed by majority of people. The rapid increase of social media in the recent past has provided end users a powerful platform to voice their opinions. Twitter, being one such platform, provides day-to-day updates on political events through different hashtags and trends. People provide their opinion by reacting on such political events. Our approach is to gather a collection of tweets of top political parties contesting within the General State election, 2022, then compute the sentiment score. Dataset contains mixture of both popular as well as recent tweets related to specific political party. Specific keywords are used to extract tweets for a party like ‘BJP elections 2022’, ‘#UPelections BJP’, ‘#Punjabelections BJP’, etc. We utilized a combination of VADER Sentiment Analyzer and classic machine learning algorithms like Random Forest Classifier, SVM, etc. to build our classifier and classify the test data as positive, negative and neutral tweets. Therefore, this work analyses tweets collected from twitter and predicts election results by performing sentimental analysis on them.

Key Words: Sentimental Analysis, Twitter, Supervised learning, Natural Language Processing, Machine Learning