Perceived algorithmic recommendation features and information fatigue among social media users

This study develops an integrated framework to examine how perceived recommendation accuracy, perceived algorithmic transparency, and perceived recommendation novelty are associated with information fatigue through perceived information overload and perceived information narrowing on social media platforms. Using survey data from 425 adult users, the study employed PLS-SEM, cIPMA, and fsQCA. The PLS-SEM results show that perceived recommendation accuracy is positively associated with both cognitive appraisals and is indirectly associated with information fatigue through them.

Perceived algorithmic transparency is positively associated with perceived information overload and indirectly associated with information fatigue through this appraisal. Perceived recommendation novelty is negatively associated with perceived information overload, perceived information narrowing, and information fatigue. Both cognitive appraisals are positively associated with information fatigue. cIPMA identifies perceived recommendation novelty as having the largest absolute total association with information fatigue, followed by perceived information overload and perceived information narrowing, while no antecedent is a necessary condition for high information fatigue. fsQCA identifies two configurations associated with high information fatigue and four with non-high information fatigue.

The findings clarify the appraisal and configurational mechanisms underlying information fatigue and offer empirically informed directions for future platform design and testing concerning relevance, novelty, diversity, and processing demands. This research was supported by the Scientific Research Planning Project of the Tianjin Municipal Education Commission (Grant No. 2024SK110), the Qingdao Binhai University Postdoctoral Innovation Practice-Based Funding Project, and the University Scientific Research Project of the Anhui Provincial Department of Education, “Research on the Formation Mechanism of Industrial Heritage Cultural Tourism Experiences in the Context of Digital Empowerment: A Case Study of Hefei Iron and Steel Plant” (Grant No. 2025AHGXSK40034). Pei Yao and Shupeng Xia contributed equally to this work.

School of Media and Art（School of International Education, Tianjin University of Sport, Tianjin, China School of Culture and Media, Anhui Xinhua University, Hefei, Anhui, China School of Business, Qingdao Binhai University, Qingdao, Shandong, China School of Business, Qingdao University, Qingdao, Shandong, China School of Business, Jiangsu Ocean University, Jiangsu, China All study procedures involving human participants followed the Helsinki Declaration. Prior to the commencement of the study, ethical approval was obtained from the Ethics Committee of Tianjin University of Sport (Approval No.: TJUS-2025-095). Informed consent was obtained from all study participants.

The study was approved by the Academic Ethics Committee of Tianjin University of Sport (Approval No. Informed consent was obtained from all participants involved in the study. The authors declare no competing interests.

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