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Recommendation Algorithm in TikTok: Strengths, Dilemmas, and Possible Directions


  • Pengda Wang


Recommendation algorithms are reshaping the ecology of digital video-sharing platforms and users' media usage behaviors. TikTok's recommender system is widely considered to be an outstanding representative among them. Although a large amount of research has been conducted in relation to TikTok, most of these studies pay attention to content analysis, platform features study, user behavior examination and technical aspects of platform algorithm. However, there is markedly less research into TikTok’s recommendation algorithm as well as relevant theoretical and empirical support for this. Based on a slightly simplified variant of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines (Page et al., 2021), this paper reviews the literature on the use of recommendation algorithm in TikTok, aiming to serve as a brief primer to answer the strengths and dilemmas of the adoption of recommendation algorithm on the TikTok platform, and to propose possible directions for short-form mobile video platforms.

Suggested Citation

  • Pengda Wang, 2022. "Recommendation Algorithm in TikTok: Strengths, Dilemmas, and Possible Directions," International Journal of Social Science Studies, Redfame publishing, vol. 10(5), pages 6066-6066, September.
  • Handle: RePEc:rfa:journl:v:10:y:2022:i:5:p:6066

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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General


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