{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T17:53:30Z","timestamp":1782237210220,"version":"3.54.5"},"reference-count":54,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T00:00:00Z","timestamp":1782172800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Behavioral Sciences"],"abstract":"<jats:p>Platform algorithms are widely used to personalize content and organize users\u2019 everyday social media experiences. Yet they may also become objects of resistance when algorithmic recommendations are perceived as intrusive, repetitive, or difficult to escape. Drawing on the critical theory of technology, this study develops a parallel mediation model to explain why users resist algorithm-driven social media platforms. Focusing on algorithmic power and algorithmic technicality as two perceived characteristics of platform algorithms, the model examines whether these perceptions are associated with algorithmic resistance through fairness evaluations and negative emotions. Based on survey data from users of Chinese algorithm-driven social media platforms, the results show that both algorithmic power and algorithmic technicality are associated with stronger algorithmic resistance through lower fairness evaluations and stronger negative emotions. These findings suggest that algorithmic resistance is not merely a response to inaccurate or opaque recommendations, but also reflects users\u2019 reactions to algorithms experienced as systems of platform control and data-driven inference. By identifying fairness evaluations and negative emotions as parallel cognitive and affective pathways, this study shifts attention from algorithmic acceptance to algorithmic resistance and provides a more critical understanding of user agency in human\u2013algorithm relations.<\/jats:p>","DOI":"10.3390\/bs16071044","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T17:11:49Z","timestamp":1782234709000},"page":"1044","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Why Users Rebel Against Algorithms: The Impact of Perceived Algorithmic Power on Fairness Evaluations, Negative Emotions, and Resistance Behaviors"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-9486-7399","authenticated-orcid":false,"given":"Yangyang","family":"Shi","sequence":"first","affiliation":[{"name":"School of Journalism and Communication, Xiamen University, Xiamen 361005, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jialu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Arts, Design & Architecture, University of New South Wales, Sydney, NSW 2052, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Journalism and Communication, Xiamen University, Xiamen 361005, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haiqing","family":"Bai","sequence":"additional","affiliation":[{"name":"School of Journalism and Communication, Xiamen University, Xiamen 361005, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"734","DOI":"10.1109\/TKDE.2005.99","article-title":"Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions","volume":"17","author":"Adomavicius","year":"2005","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Ahmmad, M., Shahzad, K., Iqbal, A., and Latif, M. 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