JOURNAL ARTICLE

Visibility of K-pop in the U.S.: Global rankings, 'audience mis-aggregation', and mainstream attention to niche genre.

  • Published In: Convergence: The Journal of Research into New Media Technologies, 2025, v. 31, n. 3. P. 862 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: Liu, Anna Yan; Taneja, Harsh 3 of 3

Abstract

This article examines how K-pop, a niche genre appealing primarily to specific audience segments, gained mainstream visibility in the U.S. market through the institutional construction of global audiences by Billboard's Social 50 chart and Top Social Artist Award. It argues that Billboard's quantification process aggregates worldwide social media engagement data without adequately accounting for regional differences in audience size and consumption cultures, resulting in a mis-aggregation that over-represents tastes from regions with large internet user bases, notably Asia and Latin America. BTS's rise to mainstream attention in the U.S. is attributed to this mis-aggregation, initially interpreted as global popularity, which was later reinterpreted as reflecting K-pop fans' data-driven consumption practices—fans strategically engaging with digital platforms to influence chart rankings. The study highlights how measurement regimes like Billboard's function as nexuses where diverse regional production and consumption cultures intersect, shaping industry narratives and prompting shifts in U.S. music production culture.

Additional Information

  • Source:Convergence: The Journal of Research into New Media Technologies. 2025/06, Vol. 31, Issue 3, p862
  • Document Type:Article
  • Subject Area:Music
  • Publication Date:2025
  • ISSN:1354-8565
  • DOI:10.1177/13548565251320755
  • Accession Number:186246043
  • Copyright Statement:Copyright of Convergence: The Journal of Research into New Media Technologies is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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