The Echo Chamber Effect: Social Media Algorithms and the Polarization of Political Discourse - Arisman Sabir; Siri Lek; Prasojo Prasojo (Journal of Social Science Utilizing Technology, 2026)
Background. The rapid expansion of social media has transformed political communication by introducing algorithmically curated information environments that shape users’ exposure to content. Concerns have emerged regarding the echo chamber effect, where individuals are predominantly exposed to ideologically aligned information, potentially intensifying political polarization and limiting deliberative discourse. Purpose. The present study aims to examine the extent to which social media algorithms contribute to the formation of echo chambers and to assess their influence on patterns of political engagement and perception. Method. A mixed-methods research design was employed, combining quantitative network analysis and survey data from 300 participants with qualitative interviews and computational analysis of platform interactions. Results. The findings indicate that algorithmic filtering significantly reinforces exposure to homogeneous content, leading to increased ideological clustering and higher levels of perceived polarization. Evidence further suggests that user attempts to diversify information sources are constrained by persistent algorithmic personalization. Conclusion. The study concludes that the echo chamber effect is a socio-technical phenomenon driven by the interaction between user behavior and algorithmic systems, with significant implications for democratic communication.