Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Jaison, Donel K.; Iyer, Lakshmi Shankar Title A name given to the resource Empowering Democracy: A Comprehensive Analysis and Predictive Modelling of Voter Turnout in Indian General Elections Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Vision; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1177/09722629251316664" target="_blank" rel="noreferrer noopener">https://doi.org/10.1177/09722629251316664</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105000139883?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105000139883?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Jaison D.K., School of Business and Management, Christ University, Karnataka, Bangalore, India; Iyer L.S., School of Business and Management, Christ University, Karnataka, Bangalore, India Description An account of the resource This study aims to break down the complex dynamics driving voter turnout in Indian general elections, providing a detailed examination of the various elements that influence voters to engage in the democratic process. It investigates how voter engagement is changing over years, looking at socio-economic factors, regional differences and historical patterns that have an impact on civic engagement. The research utilizes a detailed exploratory data analysis to examine voter data from 1952 to 2019. Key factors influencing voting turnout are identified through statistical methods and visualizations. In order to predict and comprehend voter behaviour based on various socio-demographic parameters, the study uses advanced machine learning algorithms, such as Random Forest, XGBoost, LSTM and other important models. This project contributes to the understanding of voter behaviour, providing actionable insights for improving democratic participation in the Indian electoral landscape by utilizing hyper-localized constituency-wise data. Previous studies mostly looked into the political landscape of other countries and did not use any hyper-localized data. The study reveals regional differences, socio-economic linkages and important drivers of voter turnout. It highlights the value of focused campaigns, interventions tailored to a certain region and the use of technology to increase political engagements. 2025 MDI. Subject The topic of the resource Data Analysis; Democratic Participation; Indian General Election; Machine Learning; Regional Variations; Socio-economic Factors; Voter Turnout Publisher An entity responsible for making the resource available Sage Publications India Pvt. Ltd Relation A related resource ISSN: 9722629; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Bronze Open Access Format The file format, physical medium, or dimensions of the resource online