{
  "abstract": "Political influence on social media is not confined to explicitly political spaces. We examine how UK football fan communities on Twitter became conduits for political messaging in the post-Brexit Referendum period (2016–2017). Although political tweets represented fewer than 0.1% of 152 million football-related posts, they achieved substantial amplification through network position, identity alignment, and platform dynamics. Using a hybrid approach that integrates social network analysis with iterative content filtering, we isolate 94,846 political tweets and map how political narratives entered and propagated within fan networks. We propose an analytical framework that links recurring mechanisms of political influence to observable network and content signatures, enabling the systematic identification of candidate regions for closer investigation. We identify six distinct influence mechanisms: hashtag hijacking, suspected coordinated inauthentic amplification, hybrid activism embedded within fan groups, elite political “megaphones”, media provocation and inadvertent amplification. Five case studies collectively illustrate these six mechanisms. Each mechanism exhibits characteristic network signatures, including star-like amplification hubs, tightly reciprocal clusters, and dense ideologically aligned user communities that facilitate the diffusion of political narratives. Our findings show that political messaging was not randomly dispersed but concentrated within connective nodes of the football discourse network, enabling cross-community transmission. Propagation and amplification of political messages depended less on message volume than on structural integration. Beyond documenting a historical episode, we contribute a transferable analytical pipeline and a reproducible framework for identifying candidate regions of political influence through integrated network and content analysis, providing a foundation for future automated detection approaches. Author summary: Political influence on social media is often studied in explicitly political spaces, yet much of everyday online life unfolds in communities organised around culture, sport, and shared identity. In this study, we examine how UK football fan communities on Twitter became sites of political engagement following the Brexit referendum. We combine network analysis and content analysis to identify how political messages entered and spread within a predominantly non-political environment. Rather than focusing only on individual actors or viral posts, we introduce a framework that combines network and content analysis to identify regions of online communities where recurring influence mechanisms are likely to operate. Through case studies, we show how political content was inserted into football conversations via hashtag hijacking, coordinated amplification, activist mobilisation, elite “megaphone” accounts, media-triggered provocation and inadvertent amplification. Our findings demonstrate that political influence in digital environments often operates indirectly, leveraging shared cultural identities and network structures rather than overt campaigning alone. Even low volumes of political content can achieve substantial amplification when aligned with structurally central nodes or cohesive communities. By outlining a reproducible workflow for identifying and interpreting these dynamics, we provide tools for understanding how online cultural spaces can become conduits for political influence and how such processes might be identified in other domains.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Computer Science, University of Exeter, Exeter, United Kingdom"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Helen Paffard"
    },
    {
      "name": "Diogo Pacheco"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cjfw2shar7ann.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pcsy.0000141",
  "fulltext_url": "https://journals.plos.org/complexsystems/article?id=10.1371/journal.pcsy.0000141",
  "id": "cjfw2shar7ann",
  "issns": [
    "2837-8830"
  ],
  "landing_url": "https://journals.plos.org/complexsystems/article?id=10.1371/journal.pcsy.0000141",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "plos",
      "/Biology and life sciences/Molecular biology/Interaction networks"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Behavior/Recreation/Sports"
    ],
    [
      "plos",
      "/Biology and life sciences/Sports science/Sports"
    ],
    [
      "plos",
      "/Computer and information sciences/Network analysis"
    ],
    [
      "plos",
      "/Computer and information sciences/Network analysis/Centrality"
    ],
    [
      "plos",
      "/Computer and information sciences/Network analysis/Social networks/Social media/Twitter"
    ],
    [
      "plos",
      "/Engineering and technology/Signal processing/Signal amplification"
    ],
    [
      "plos",
      "/Social sciences/Political science/Elections"
    ],
    [
      "plos",
      "/Social sciences/Psychology/Behavior/Recreation/Sports"
    ],
    [
      "plos",
      "/Social sciences/Sociology/Communications/Social communication/Social media/Twitter"
    ],
    [
      "plos",
      "/Social sciences/Sociology/Culture"
    ],
    [
      "plos",
      "/Social sciences/Sociology/Social networks/Social media/Twitter"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://journals.plos.org/complexsystems/article/file?id=10.1371/journal.pcsy.0000141&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/cjfw2shar7ann.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T12:20:55Z",
      "native_id": "10.1371/journal.pcsy.0000141",
      "source": "plos",
      "url": "https://journals.plos.org/complexsystems/article?id=10.1371/journal.pcsy.0000141"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "plos:molecular biology",
      "subfield": "molecular-biology"
    }
  ],
  "title": "Kicking politics: Towards a framework for detecting political influence in online communities",
  "title_text": "Kicking politics: Towards a framework for detecting political influence in online communities",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T12:20:45Z",
  "url": "https://research.draconitic.com/paper/cjfw2shar7ann",
  "venue": "PLOS Complex Systems",
  "versions": []
}