The Role of Algorithmic Content Filtering in Fragmented Football Fan Loyalty with Mediating Role of Cultural Representation and the Moderating Role of Algorithmic Literacy

Document Type : Research Paper

Authors

1 Department of Sport Management, Ka.C., Islamic Azad University, Karaj, Iran

2 Department of Sport Management,, Karaj branch, Islamic Azad University, Karaj, Iran.

10.22059/jsm.2026.420887.3674
Abstract
Introduction: The rapid proliferation of algorithmic content filtering in social media platforms has fundamentally transformed the sports fandom experience, yet the mechanisms through which algorithmic filtering affects fan loyalty remain unclear. This study aimed to investigate the role of algorithmic content filtering in fragmented fan loyalty, with perceived cultural representation as a mediator and algorithmic literacy as a moderator, among fans of Persepolis and Esteghlal.

Methods: A quantitative, cross-sectional survey design was employed. Data were collected from 489 digitally active fans through convenience and voluntary sampling and analyzed using partial least squares structural equation modeling (PLS-SEM).

Results: Algorithmic content filtering positively influenced perceived cultural representation (β = 0.458, p < 0.001), and perceived cultural representation positively influenced fragmented fan loyalty (β = 0.362, p < 0.001). The mediating role of cultural representation (β = 0.166, p < 0.001) and the moderating role of algorithmic literacy (β = -0.197, p < 0.001) were confirmed. The model explained 53.6% of the variance in fragmented fan loyalty.

Conclusion: Algorithmic content filtering leads to fragmented fan loyalty through perceived cultural representation, and algorithmic literacy weakens this relationship. Sports clubs can mitigate the negative consequences of unequal filtering by enhancing algorithmic transparency and promoting algorithmic literacy among fans.

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Articles in Press, Accepted Manuscript
Available Online from 11 November 2026

  • Receive Date 01 September 2026
  • Revise Date 25 September 2026
  • Accept Date 25 September 2026