Understanding Voter Behavior With Predictive Modeling

Understanding voter behavior and improving election prediction are vital for strengthening democratic processes and fostering informed political engagement. Advances in artificial intelligence, machine learning, and sophisticated polling methodologies enable more accurate insights into electoral dynamics across diverse political systems. These tools not only help forecast outcomes but also reveal patterns of participation, public sentiment, and policy influence. By integrating data-driven analysis with comparative political research, society gains the ability to enhance transparency, refine campaign strategies and better anticipate the needs and concerns of the electorate. Understanding Voter Behavior With Predictive Modeling unites cutting-edge research from across the globe to illuminate contemporary trends in electoral analysis. It showcases innovative approaches that leverage predictive models, artificial intelligence, and polling methodologies to advance the study of electoral behavior. Covering topics such as big data, party loyalty, and populist campaigns, this book is an excellent resource for academicians, data scientists, policy analysts, electoral consultants, political marketing experts, and more.

Author Biography

Georgia Panagiotidou holds a PhD in Political Sciences with a specialization in applied political analysis. She has been teaching since 2016 at the School of Political Sciences of Aristotle University of Thessaloniki, as well as in the postgraduate program “Governance and Regional Development” as an academic scholar and adjunct lecturer. Additionally, she teaches as Collaborating Teaching Staff in the postgraduate program “Public Administration and Electronic Governance” at HOU and is a postdoctoral researcher in the Horizon Europe – AI4GOV program on artificial intelligence in governance. Her research interests and scientific activity focus on the analysis of political competition, parties, and electoral behaviour, and the identification of typologies of voters, candidates, parties, and issues using comparative data analysis methods under the “Candidates-Parties- Issues” scheme. She participates in research projects at the Laboratory of Applied Political Analysis of AUTH, she was member of the research team for Greece’s first electronic Voting Advisor Application (VAA) in 2010 (helpmevote.gr) and participated in the COST True European Voter research project. Furthermore, she has conducted extensive empirical comparative research on political and electoral behaviour in Greece and at a pan-European level on behalf of European Union entities. She systematically participates in international scientific conferences with presentations of her research work and has published her scientific works in scientific journals and collective volumes. She is a member of the Hellenic, American, and International Political Science Associations (HPSA, APSA, IPSA), the International Federation of Classification Societies (IFCS), and the Greek Society for Data Analysis (GSDA).