Cited by 40Misinformation and Its ImpactsSocial Media and PoliticsSpam and Phishing Detection

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Brexit and bots: characterizing the behaviour of automated accounts on Twitter during the UK election

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Abstract

Online Social Networks (OSNs) offer new means for political communications that have quickly begun to play crucial roles in political campaigns, due to their pervasiveness and communication speed. However, the OSN environment is quite slippery and hides potential risks: many studies presented evidence about the presence of d/misinformation campaigns and malicious activities by genuine or automated users, putting at severe risk the efficiency of online and offline political campaigns. This phenomenon is particularly evident during crucial political events, as political elections. In the present paper, we provide a comprehensive description of the networks of interactions among users and bots during the UK elections of 2019. In particular, we focus on the polarised discussion about Brexit on Twitter, analysing a data set made of more than 10 millions tweets posted for over a month. We found that the presence of automated accounts infected the debate particularly in the days before the UK national elections, in which we find a steep increase of bots in the discussion; in the days after the election day, their incidence returned to values similar to the ones observed few weeks before the elections. On the other hand, we found that the number of suspended users (i.e. accounts that were removed by the platform for some violation of the Twitter policy) remained constant until the election day, after which it reached significantly higher values. Remarkably, after the TV debate between Boris Johnson and Jeremy Corbyn, we observed the injection of a large number of novel bots whose behaviour is markedly different from that of pre-existing ones. Finally, we explored the bots’ political orientation, finding that their activity is spread across the whole political spectrum, although in different proportions, and we studied the different usage of hashtags and URLs by automated accounts and suspended users, targeting the formation of common narratives in different sides of the debate.

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References 65 · Cited by 40

Research works printed but not linked: 1

  1. Bradshaw S, Howard P (2018) How does junk news spread so quickly across social media? Algorithms, advertising and exposure in public life. White Paper, Oxford Internet Institute

Metadata

Authors
Bruno, M., Lambiotte, R., & Saracco, F.
Affiliations
  • IMT School for Advanced Studies Lucca (IT)
  • University of Oxford (GB)
Corresponding author
Bruno, Matteo
Venue
EPJ Data Science
Published
2022-03-22
Volume
11
Issue
1
Pages
17-17
ISSN
2193-1127 (ISSN-L)
OpenAlex
W3186413058
Cited by
40
References
65
Citations by year
2026: 6 · 2025: 7 · 2024: 16 · 2023: 8 · 2022: 3
FWCI
12.22
Type
journal article
Language
en
Open access
Locations
  • EPJ Data Science (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • european commission (871042)
  • imt school for advanced studies lucca (Frontier Proposal Fellowship 2020)
  • scuola internazionale superiore di studi avanzati (PAI project TOFFEE)
Topics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Social Sciences › Communication › Social Media and Politics
  • Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
Keywords
automated accounts, bots, Twitter, Brexit, 2019 UK general election, political polarization, misinformation, political campaigns, hashtags, URLs, television debates, Boris Johnson, Jeremy Corbyn, online political communication

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