Perceived Algorithmic Personalization of Short-Videos and Digital Media Addiction

In the era of mobile internet, short-video services have become a major source of digital entertainment and information for adolescent groups. Short-video platforms rely on algorithm-driven content distribution. Based on users' viewing records, likes, and comments, recommendation systems deliver content matching individual interests and reshape how adolescents receive online information. Meanwhile, many adolescents cannot control their short-video usage, and the problem of digital-media addiction has drawn increasing attention from communication and youth-psychology researchers. This literature review adopts the user subjective-perception perspective. It sorts out the operating logic of algorithm-driven personalized recommendation, defines the concept and real-life manifestations of adolescent digital-media addiction, and discusses the connection between perceived algorithmic personalization and digital-media addiction. The review finds that personalized recommendations improve user experience but strengthen continuous short-video-browsing behaviors through variable-reward mechanisms, raising adolescents' risk of digital-media addiction. Most existing studies focus on objective algorithm functions, while empirical discussions about adolescents' subjective perceptions remain limited. This paper summarizes existing research gaps and offers references for future studies on adolescent media use.