Role of Likes and Dislikes in Influencing User Behaviors on Social Media

• 成果类型: Article
• 署名作者: Turel, Ofir; Qahri-Saremi, Hamed
• 署名单位: University of Melbourne; Colorado State University System; Colorado State University Fort Collins
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222
• DOI: 10.1080/07421222.2024.2340829
• 发表日期: 2024
• 页码: 515-545
• 关键词: NETWORKING SITES; fake news; online; responses; reward; RISK; pain; antecedents; PERSPECTIVE; engagement

摘要

Two recent changes on social media platforms include (1) allowing users to mask the number of likes on others' posts, aimed at reducing social comparisons and consequent technology-mediated dangerous behaviors (TMDBs), such as disclosing private information, and (2) adding a dislike reaction, aimed at increasing engagement. Nevertheless, the effects of these changes on user behaviors are unclear. In this paper, we seek to address this gap by integrating risk-sensitivity theory (RST) and prospect theory. First, we explain that while masking others' likes may reduce social comparison, based on the homeostatic violation concept, people also make internal comparisons to expectations. Undesirable deviations from users' expectations of likes and dislikes (e.g., too few likes or too many dislikes) can motivate TMDBs that users believe can alleviate the undesirable deviations. Thus, we argue that, in addition to social comparison mechanisms, there is an internal comparison mechanism that can motivate TMDBs. We test these claims via five randomized controlled experiments (total n = 1,594). Results show that, beyond social comparison mechanisms, receiving too few likes or too many dislikes, compared to internal expectations, can motivate TMDBs. Moreover, we found that losses loom larger than gains as users are more likely to engage in TMDBs to avoid excess dislikes than to avoid deprivation of likes. These findings make novel contributions to social media research and practice by pointing to an internal comparison mechanism as a potent motivator of TMDBs beyond social comparison processes and to the higher toxicity of dislikes than likes in terms of inciting TMDBs on social media.