The Impact of Social Fake News on Different Groups of People-Take TikTok and Kuaishou for Example

Abstract

This study focuses on TikTok and Kuaishou platforms. Through quantitative analysis and case study methods, it analyzes the transmission law and influence mechanism of social fake news in different user groups. The transmission law refers to the patterns and dynamics of how fake news spreads within and across different user groups. First, this paper defines the types and characteristics of fake health news and constructs a theoretical framework of influencing factors based on the psychological acceptance model. Secondly, the data on TikTok and Kuaishou platforms were collected, and SPSS software was used for multivariate statistical analysis, which revealed how factors such as cognitive bias, decision pressure, group effect, and algorithm recommendation mechanism affected people’s acceptance and response to fake news. Further, the study analyzed the influence of teenagers, adults, and elderly groups psychological and behavioral differences and found that teenagers are more vulnerable to web celebrity effect and peer pressure, and adults' health information and processing ability is relatively strong, the elderly, by media habits and trust differences to health information receive more sensitive. The case study reveals how the platform algorithm recommendation mechanism affects the transmission path and influence of information. Finally, this paper puts forward relevant suggestions according to the research results, including strengthening media literacy education, optimizing the supervision of social platforms, cultivating the public self-protection mechanism, and improving the policy-level countermeasures so as to deal with the challenge of health fake news jointly.