Behavioural influence of TikTok’s algorithm recommendations on users’ engagement and users’ self-persuasion / Siti Khadijah Amir Hamzah, Ahlam Abdul Aziz and Shazleen Mohamed

This study examines how TikTok's algorithm influences user behaviour, particularly in user engagement and self-persuasion. The algorithm recommends content based on user interactions, but its opaque nature complicates understanding of how it prioritizes content and potential biases. These biases can reinforce specific behaviours and viewpoints, create echo chambers, and influence users' self-perception. By focusing on maximizing engagement, the algorithm can also promote addictive behaviours, impact mental health, shorten attention spans, and disrupt daily activities. The research aims to achieve the following objectives: (1) identify the level of behavioural influence exerted by TikTok's algorithm on users, (2) examine the level of users' engagement in response to TikTok algorithm recommendations among users, (3) identify level of users' self-persuasion influenced by the algorithm, (4) identify the relationship between behavioural influence and users' engagement, and (5) identify the relationship between behavioural influence and users' self-persuasion. Using quantitative methods and stratified sampling, this study analyses data from 385 Millennial and Generation Z TikTok users in the Klang Valley, Malaysia. An online survey conducted via Google Forms captures users' experiences and perceptions regarding TikTok's algorithm. Overall, the findings conclude that TikTok is a persuasive platform, as the results reveal a significant relationship between behavioural influence and both user engagement and self-persuasion. This study highlights the substantial impact of TikTok's algorithm on user behaviour, offering valuable insights for social media managers. However, a primary limitation is the short timeframe, which resulted in data collection from only 203 respondents.