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Kicking Politics: How Football Fan Communities Became Arenas for Political Influence

Helen Paffard, Diogo Pacheco

TL;DR

The paper investigates how political campaigns mobilized UK football fan communities on Twitter during 2016–2017, using a hybrid network- and content-analysis approach across four network types to map political discourse onto football conversations. It reveals that football spaces, though not highly political by volume, host dense, interconnected discourse with influential actors driving amplification through hashtag hijacking, embedded activism, and political megaphones. Three case studies illustrate concrete influence mechanisms and how club-affiliated fans can act as vectors for broader political narratives. The study contributes a framework for detecting and understanding political influence in non-political online spaces, with implications for safeguarding democratic discourse and designing resilience against manipulation.

Abstract

This paper investigates how political campaigns engaged UK football fan communities on Twitter in the aftermath of the Brexit Referendum (2016-2017). Football fandom, with its strong collective identities and tribal behaviours, offers fertile ground for political influence. Combining social network and content analysis, we examine how political discourse became embedded in football conversations. We show that a wide range of actors -- including parties, media, activist groups, and pseudonymous influencers -- mobilised support, provoked reactions, and shaped opinion within these communities. Through case studies of hashtag hijacking, embedded activism, and political "megaphones", we illustrate how campaigns leveraged fan cultures to amplify political messages. Our findings highlight mechanisms of political influence in ostensibly non-political online spaces and point toward the development of a broader framework in future work.

Kicking Politics: How Football Fan Communities Became Arenas for Political Influence

TL;DR

The paper investigates how political campaigns mobilized UK football fan communities on Twitter during 2016–2017, using a hybrid network- and content-analysis approach across four network types to map political discourse onto football conversations. It reveals that football spaces, though not highly political by volume, host dense, interconnected discourse with influential actors driving amplification through hashtag hijacking, embedded activism, and political megaphones. Three case studies illustrate concrete influence mechanisms and how club-affiliated fans can act as vectors for broader political narratives. The study contributes a framework for detecting and understanding political influence in non-political online spaces, with implications for safeguarding democratic discourse and designing resilience against manipulation.

Abstract

This paper investigates how political campaigns engaged UK football fan communities on Twitter in the aftermath of the Brexit Referendum (2016-2017). Football fandom, with its strong collective identities and tribal behaviours, offers fertile ground for political influence. Combining social network and content analysis, we examine how political discourse became embedded in football conversations. We show that a wide range of actors -- including parties, media, activist groups, and pseudonymous influencers -- mobilised support, provoked reactions, and shaped opinion within these communities. Through case studies of hashtag hijacking, embedded activism, and political "megaphones", we illustrate how campaigns leveraged fan cultures to amplify political messages. Our findings highlight mechanisms of political influence in ostensibly non-political online spaces and point toward the development of a broader framework in future work.

Paper Structure

This paper contains 20 sections, 4 figures, 1 table.

Figures (4)

  • Figure 1: Hashtag Co-Occurrence Network and Discourse Topic Communities. Network of football- and politics-related hashtags with $>25$ co-occurrences. Hashtags are interwoven, with some football hashtags strongly linked to specific discourse topics. Node colour indicates community; node size reflects weighted degree. Zoom recommended for detailed inspection.
  • Figure 2: Hashtag and User Similarity Networks. One-mode projections of a user–hashtag bipartite matrix capturing topical alignment among users and hashtags. (A) Hashtag similarity network with nodes coloured by overarching discourse theme (Political, Football, UK, General). (B) User similarity network with nodes coloured by user community.
  • Figure 3: User Retweet Network and Top Influencers. Node size represents PageRank; node colour indicates community. Zoom in for a detailed inspection. Right: Top 20 influencers by actor type and in-degree across interaction sub-networks (RT: retweet; Q: quote; R: reply; M: mention). Actor prominence varied by interaction type.
  • Figure 4: Left-Leaning User Community Characterisation. Polar plots display user community tweets per hashtag communities and overarching discourse theme. The two user communities centred on Labour Party politics and Jeremy Corbyn.