Predicting elections over Twitter: a campaign strategies of political parties using machine learning algorithms Online publication date: Tue, 12-Apr-2022
by G. Anuradha; Nageswara Rao Moparthi; Sridhar Namballa
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 21, No. 3/4, 2022
Abstract: Twitter is a social networking web application built to find out what is happening around us and all over the world. For this study, we analysed one million tweets for applying sentiment analysis is helpful to analyse the information where opinions are either good or bad/negative, or neutral and highly structured, heterogeneous in some cases. In this article we used a few machine learning algorithms like naïve Bayes, support vector machine, decision tree and neural network for analysis of elections results. Twitter data is used to predict the outcome of election by collecting data and analysing sentiments about the candidates. The experiential results show that the winning party's electoral success is expressively associated with social media/Twitter. It is a main promotional tool for new and upcoming parties in the 2019 general elections. This article mainly focused on Karnataka state elections of 2018 month of May for examining the analytical power of Twitter.
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