Paper Title
PREDICTING VOTER BEHAVIOR AND SENTIMENTS IN INDIAN GENERAL ELECTION-2024 USING BIG DATA

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