The Indifference of Curation: How Social Media Algorithms Shape the Perception of Racial Identity in Youth

Since 2016, the rise of algorithmically curated short-form content on Instagram, TikTok, and YouTube has transformed how young Americans encounter racial discourse online, yet the specific role of algorithms on shaping racial identity remains underexamined. This paper investigates how algorithmically curated racism on these three platforms has contributed to the perception of racial identity among people 18 years old or younger in the United States. I draw on both an extensive literature review as well as a discourse analysis of viral short-form videos and their comment sections to exemplify the proliferation of racism on each platform. The findings reveal that algorithms curate and amplify racially-charged content as an unintended byproduct of engagement-based optimization, allowing hateful comments to surface to the top of comment sections regardless of their content, and covert, humor-coded racism to spread largely untouched. This paper introduces two theoretical frameworks to explain the resulting effects on adolescent users: engagement-indifferent amplification, which describes platforms’ structural inability to distinguish racially harmful content with any other kind, and algorithmic identity conditioning, which outlines how repeated exposure to racial content shapes adolescents’ developing racial identity. Together, these findings suggest that the commercial drivers of algorithmic curation on these platforms are not aligned with the developmental perspectives on society of their youngest users, with many significant implications for ongoing debates over social media regulation and youth online safety.