Facebook's Machine Learning Algorithms and Voting Behavior: An Analytical Study

Author(s)	Mr. vineet kumar, Dr. Manaswi Semwal
Country	India
Abstract	In contemporary democratic societies, Facebook has evolved beyond being merely a social networking platform; it has emerged as a powerful medium influencing political information, opinion formation, and voter behavior. Through machine learning algorithms, Facebook analyzes users' interests, activities, and behavioral patterns, subsequently presenting political content tailored to these specific profiles. The objective of this research is to understand how processes such as algorithmic selection, personalized political advertising, and phenomena like "filter bubbles" and "echo chambers" impact voters' political perceptions and voting behavior. The study also highlights how machine learning-based algorithms can steer voters toward specific political ideologies, thereby exerting a profound influence on democratic decision-making processes. This research aims to elucidate the interrelationship between the role of Facebook algorithms, voter psychology, and digital political communication. In conclusion, this study demonstrates that machine learning-based algorithms are reshaping the flow of information and voting behavior within democracies, with significant socio-political ramifications.
Keywords	Facebook, Machine Learning, Voting Behavior
Field	Arts
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-04-03
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.73502

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