ALGORITHMIC POPULISM: HOW TIKTOK'S RECOMMENDATION ARCHITECTURE SHAPES YOUTH POLITICAL POLARIZATION

Abstract

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This paper examines how the recommendation architecture of TikTok contributes to the polarization of young people in politics. The emergence of social media in the age of digital media domination defines the nature of political discourse where Tik Tok filters and selects content to impact the agenda. This study examines the potential of TikTok recommendation systems to cause political division especially among the Gen Z generation by amplifying the extreme and forming echo chambers. On the basis of prior theories of the existence of algorithmic bias and political polarization, the current research is expected to reveal how TikTok algorithms have led young individuals to become interested in political content. The paper provides a mixed-method analysis of how Tik Tok algorithm creates a partisan space which can increase partisan tendencies of youth through the use of data analytics of user interactions and qualitative surveys. The results indicate that there is a high level of association between the exposure to content that is driven by algorithms and enhanced political polarization among users, which validates the critical role played by algorithmic populism in defining the political behavior of users. The paper emphasizes that algorithmic governance should be reconsidered to reduce all the adverse effects on democracy.