Boosting popularity: Folk theories and algorithmic resistance of visibility contests in the comment sections.
This study examines the collective actions of Chinese netizens in contesting algorithm visibility through popularity-boosting comments. Employing a netnographic approach within the theoretical frameworks of algorithm resistance and folk theories, the research analyzes popularity-boosting comments (N...
| Published in: | Big Data & Society Vol. 12; no. 2; pp. 1 - 15 |
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| Format: | Article |
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Sage Publications Inc.
Apr-Jun2025
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=186840166&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 186840166 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 20539517 KG5N jtl: Big Data & Society issn: 20539517 maglogo: Y pubinfo: dt: Apr-Jun2025 vid: 12 iid: 2 pid: 344 pub: Sage Publications Inc. artinfo: ui: 186840166 10.1177/20539517251331949 ppf: 1 ppct: 14 formats: tig: atl: Boosting popularity: Folk theories and algorithmic resistance of visibility contests in the comment sections. aug: au: Zhao, Guoning affil: Institute of Communication Studies, Communication University of China, Beijing, China su: Chinese people Collective action Internet users Conflict theory Negotiation sug: subj: Chinese people Collective action Internet users Conflict theory Negotiation keyword: algorithmic resistance Boosting popularity (Dingredu) Chinese social media comment sections folk theory visibility contests ab: This study examines the collective actions of Chinese netizens in contesting algorithm visibility through popularity-boosting comments. Employing a netnographic approach within the theoretical frameworks of algorithm resistance and folk theories, the research analyzes popularity-boosting comments (N = 900) and discussions regarding these practices (N = 492) on Douyin, Xiaohongshu, and Weibo. The findings reveal that algorithmic resistance effectively sustains the lifecycle of posts and extends their dissemination. Netizens primarily engage in this resistance along two pathways: Within and beyond the algorithmic framework. Within the framework, conflicting folk theories trigger netizens' internal power struggles, undermining the consistency and continuity of collective algorithmic resistance. Beyond the algorithmic framework, strategies such as creating viral memes and manually commenting on popular posts about trending events introduce innovative forms of algorithmic resistance. However, overall, regardless of whether within or beyond the algorithmic framework, netizens' algorithmic resistance behavior is characterized by internal conflicts and relatively loose collective action. This study offers new insights into expanding the concept of algorithmic resistance, enriching the collective algorithmic resistance behaviors of netizens, and the negotiation of conflicting folk theories within those groups. It provides important implications for future research on the complex power struggles between algorithms and netizens. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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