Paper Title :Predicting Voter Behavior and Sentiments in Indian General Election-2024 Using Big Data
Author :Sanjay B. Patel, Jyotendra Dharwa, Chandrakant Patel, Luhar Dhruv
Article Citation :Sanjay B. Patel ,Jyotendra Dharwa ,Chandrakant Patel ,Luhar Dhruv ,
(2024 ) " Predicting Voter Behavior and Sentiments in Indian General Election-2024 Using Big Data " ,
International Journal of Management and Applied Science (IJMAS) ,
pp. 30-36,
Volume-10,Issue-6
Abstract : This research paper explores the potential of big data in predicting user behavior and voters' sentiments leading
up to the 2024 India Election. Social media has resulted in vast amounts of data that can provide insights into public opinion
and political preferences. By using advanced analytics such as sentiment analysis and machine learning, researchers can
uncover patterns in voter behavior. The study specifically utilizes data from social media platforms, particularly Twitter.
This data is cleaned and structured for analysis. Researchers identify key variables associated with user behavior and
sentiment through feature extraction techniques. Subsequently, machine learning models are developed to forecast voter
sentiment and behavior for the upcoming election. These models utilize historical data to project future trends, offering
valuable insights for political decision-makers. This research demonstrates the efficiency of big data to grasp and predict
voter behavior, potentially informing political campaigns and policy-making strategies for the 2024 India Election. The
study assumes two distinct algorithms, Support Vector Machines (SVM) and Naive Bayes for data prediction.The algorithms
such as SVM and NB achieved the accuracy 79.50% and 69.75% respectively.
Keywords - Voter Sentiment Prediction, Social Media, SVM, Naive Bayes
Type : Research paper
Published : Volume-10,Issue-6
Copyright: © Institute of Research and Journals
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Published on 2024-09-27 |
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