<![CDATA[Social media platforms such as Instagram, TikTok, and YouTube have become central arenas for constructing political perceptions and influencing voter behavior in the digital era. This study addresses the issue of how algorithm-driven content personalization on these platforms shapes political narratives, potentially leading to filter bubbles and echo chambers that reinforce ideological bias and limit political diversity. The objective of this research is to examine the role of social media algorithms, digital political communication strategies, and user interactions in shaping voters’ political understanding and decision-making. Using a qualitative descriptive approach, the study collects data through in-depth interviews, digital content analysis, and observations of user behavior on major social platforms during political campaigns. The theoretical framework is grounded in McQuail’s Mass Communication Theory, Social Construction of Reality, the Public Sphere, Connectivism, and Network Society. Findings indicate that algorithmic filtering significantly influences how users access and interpret political content, contributing to increased polarization. Voters are no longer passive recipients but active participants in shaping and disseminating political discourse. The study highlights that while social media enhances democratic engagement, it also poses challenges such as disinformation, ethical concerns, and the erosion of inclusive political dialogue. These dynamics necessitate stronger digital literacy and regulatory frameworks to safeguard political communication in the digital public sphere.]]>
