A SYSTEMATIC REVIEW OF ALGORITHMIC AMPLIFICATION AND HEALTH MISINFORMATION ON SHORT VIDEO PLATFORMS

Abstract

The rapid growth of short video platforms such as TikTok and Douyin has significantly transformed digital health communication. While these platforms democratize information access, they also accelerate the spread of health misinformation through algorithmic amplification. This study systematically reviews 30 peer-reviewed studies published between 2018 and 2024 to examine the mechanisms through which algorithms contribute to the dissemination of misleading medical content. Using PRISMA-based selection, studies were analyzed across three themes: algorithmic mechanisms, user behavior, and platform affordances. Findings reveal that engagement-driven recommendation systems, combined with psychological biases and visual content design, amplify misinformation at scale. The study highlights critical research gaps, including limited longitudinal analysis and insufficient evaluation of AI-based moderation. The paper concludes with implications for policy, platform design, and future research.