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Memeing the moniker: the stickiness of gang myths in Swedish news legacy media and TikTok
Umeå University, Faculty of Social Sciences, Department of Sociology. (Digsum)ORCID iD: 0000-0003-3665-2476
Umeå University, Faculty of Social Sciences, Department of Sociology.ORCID iD: 0000-0003-2500-1686
(English)Manuscript (preprint) (Other academic)
Abstract [en]

With the rise of explosive violence in urban Sweden, gang-related crime has become a dominant theme in Swedish media and political discourse. As individual members of prominent criminal networks gain increasing media attention, the construction of the gang myth—how gangs and their members are represented, circulated, and reimagined—becomes a crucial area of inquiry. This article investigates the ways in which crime content moves through the hybrid news cycle, shaping public perceptions of gangs and their leaders. Using topic modeling of news articles (n=521) and multimodal critical discourse analysis of TikTok posts (n= 73) referencing one of the most well-known gang leader, the Kurdish Fox, we examine how myth-building operates across different media contexts. Our findings reveal a stark contrast in narrative strategies: while news media frame gangs through urgency, fear, and political crisis, TikTok users engage in playful, dissident humor—employing memes, emojis, and remix culture to subvert dominant crime discourses.

Keywords [en]
Gang myths, legacy media, memes, organized crime, TikTok
National Category
Criminology Media and Communications
Identifiers
URN: urn:nbn:se:umu:diva-243049DOI: 10.31235/osf.io/sqmpd_v1OAI: oai:DiVA.org:umu-243049DiVA, id: diva2:1988948
Funder
Swedish Research Council, 2022-05414
Note

Accepted for publication in New Media & Society.

Original Publication Date: 2025-08-13

License: CC-BY Attribution-Non Commercial-No Derivatives 4.0 International 

Available from: 2025-08-14 Created: 2025-08-14 Last updated: 2025-08-14Bibliographically approved

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Eriksson Krutrök, MoaMitchell, Jeffrey

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
  • en-GB
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • text
  • asciidoc
  • rtf