Volume 2 - Issue 3, May - June 2026

Algorithms on social media sites decide what content users see in their feeds. The main purpose of these algorithms is to keep people interested by showing them posts that they are more likely to like, share, or comment on. However, this system can also cause problems in online political discussions. Algorithms often promote content that is emotional, dramatic, or strongly opinionated, because this type of content gets more views. As a result, users might mostly see posts that agree with their existing beliefs. This can lead to echo chambers, where people only hear the same opinions and rarely see things from a different point of view. Over time, this can make politics more divided and make online discussions less open. This study looks at how algorithms on social media affect political polarization. The study starts by looking at research papers, articles, and real-world examples from fields like political science and media studies. These sources help us understand how recommendation systems work and how they might affect the political content people see online. This research goes beyond a simple literature review; it also includes the development of a machine learning model. This model is trained on social media data to find patterns in political posts, how users interact with them, and how opinion-based information spreads. The results show that algorithms designed to maximize engagement often promote more extreme or emotionally charged content because it gets more user interaction. This can strengthen existing beliefs, reduce openness to new ideas, and speed up the spread of misleading information. In addition, the machine learning analysis shows that users who frequently engage with political content tend to see more of the same type of content over time. The research findings indicate that while algorithms contribute to content personalization, their unchecked application could intensify political polarization. To mitigate these potential dangers, the study advocates for increased algorithm transparency, the implementation of more robust regulations for online platforms, and the promotion of digital literacy, thereby enabling users to better understand and critically evaluate the information encountered online.

Ankush Sharma, Bhupesh Relan, Chirag, Anuj,"Social Media Algorithm and Political Polarization" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(3): Page(298-302) May-June 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.