Lv Xing, Chen Yang, Guo Weiqi
School of Journalism and Communication, Renmin University of China, Beijing, China.
Front Psychol. 2022 Apr 25;13:859597. doi: 10.3389/fpsyg.2022.859597. eCollection 2022.
Adolescents have gradually become a vital group of interacting with social media recommendation algorithms. Although numerous studies have been conducted to investigate negative reactions (both psychological and behavioral reactance) that the dark side of recommendation algorithms brings to social media users, little is known about the resistance intention and behavior based on their agency in the daily process of encountering algorithms. Focusing on the concept of algorithm resistance, this study used a two-path model (distinguishing resistance willingness and resistance intention) to investigate the algorithmic resistance of rural Chinese adolescents ( = 905) in their daily use of short video apps. The findings revealed that the perceived threat to freedom, algorithmic literacy, and peer influence were positively associated with the resistance willingness and intention; while the independent psychology on algorithmic recommendations significantly weakened resistance willingness and intention. Furthermore, this study verified the mediating role of resistance willingness and intention between the above independent variables and resistance behavior. Additionally, the positive impact of resistance willingness on resistance intention was confirmed. In conclusion, this study offers a comprehensive approach to further understanding adolescents' algorithmic resistance awareness and behavior by combining psychological factors, personal competency, and interpersonal influences, as well as two types of resistance reactions (rational and irrational).
青少年逐渐成为与社交媒体推荐算法互动的重要群体。尽管已经进行了大量研究来调查推荐算法的阴暗面给社交媒体用户带来的负面反应（心理和行为反抗），但对于他们在日常接触算法过程中基于自身能动性的抵抗意图和行为却知之甚少。本研究聚焦于算法抵抗的概念，采用双路径模型（区分抵抗意愿和抵抗意图）来调查中国农村青少年（ = 905）在日常使用短视频应用时的算法抵抗情况。研究结果表明，感知到的自由威胁、算法素养和同伴影响与抵抗意愿和意图呈正相关；而对算法推荐的独立心理则显著削弱了抵抗意愿和意图。此外，本研究验证了抵抗意愿和意图在上述自变量与抵抗行为之间的中介作用。此外，还证实了抵抗意愿对抵抗意图的积极影响。总之，本研究通过结合心理因素、个人能力和人际影响以及两种抵抗反应（理性和非理性），提供了一种全面的方法来进一步理解青少年的算法抵抗意识和行为。
