Cited by 378Misinformation and Its ImpactsSocial Media and PoliticsSpam and Phishing Detection

Political Astroturfing on Twitter: How to Coordinate a Disinformation Campaign

Open access
Keller, Franziska B., Schoch, David, Stier, Sebastian, Yang, JungHwan·2020·Political Communication

Abstract

Political astroturfing, a centrally coordinated disinformation campaign in which participants pretend to be ordinary citizens acting independently, has the potential to influence electoral outcomes and other forms of political behavior. Yet, it is hard to evaluate the scope and effectiveness of political astroturfing without “ground truth” information, such as the verified identity of its agents and instigators. In this paper, we study the South Korean National Information Service’s (NIS) disinformation campaign during the presidential election in 2012, taking advantage of a list of participating accounts published in court proceedings. Features that best distinguish these accounts from regular users in contemporaneously collected Twitter data are traces left by coordination among astroturfing agents, instead of the individual account characteristics typically used in related approaches such as social bot detection. We develop a methodology that exploits these distinct empirical patterns to identify additional likely astroturfing accounts and validate this detection strategy by analyzing their messages and current account status. However, an analysis relying on Twitter influence metrics shows that the known and suspect NIS accounts only had a limited impact on political social media discussions. By using the principal-agent framework to analyze one of the earliest revealed instances of political astroturfing, we improve on extant methodological approaches to detect disinformation campaigns and ground them more firmly in social science theory.

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Crossref · 10.1080/10584609.2019.1661888

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35 of 35 references verified0 citation errors · 0 not checkable

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  • For Keller et al. (2020), another key characteristic of astroturfing is its reliance on centralized coordination, especially for disseminating and sharing information.

    “For Keller et al. (2020), another key characteristic of astroturfing is its reliance on centralized coordination, especially for disseminating and sharing information”
  • Astroturfing is most frequently equated with political or commercial communications strategy.

    “Astroturfing is most frequently equated with political or commercial communications strategy”
  • Traditional social bots often follow pre-defined instructions to perform simplistic tasks, such as spamming, following others, and amplifying certain narratives.

    “Traditional social bots often follow pre-defined instructions to perform simplistic tasks, such as spamming (Yang et al., 2019), following others, and amplifying certain narratives (Keller et al., 2020).”

    From Anatomy of an AI-powered malicious social botnet (2024) · cites this paper as Keller et al., 2020

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Authors
Keller, F. B., Schoch, D., Stier, S., & Yang, J.
Affiliations
  • Hong Kong University of Science and Technology (HK)
  • University of Manchester (GB)
  • GESIS - Leibniz Institute for the Social Sciences (DE)
  • University of Illinois Urbana-Champaign (US)
Corresponding author
Stier, Sebastian
Venue
Political Communication
Published
2019-10-26
Volume
37
Issue
2
Pages
256-280
ISSN
  • 1058-4609 (ISSN-L)
  • 1091-7675
OpenAlex
W2971881481
Cited by
378
References
46
Citations by year
2026: 53 · 2025: 56 · 2024: 71 · 2023: 53 · 2022: 59 · 2021: 41 · 2020: 45
FWCI
73.01
Type
journal article
Language
en
Open access
Locations
  • Political Communication (publishedVersion)
  • Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) (submittedVersion)
  • BORIS (University Library Bern) (submittedVersion)
  • Research Explorer (The University of Manchester) (submittedVersion, other-oa)
  • Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
Funders
National Research Foundation of Korea (NRF-2016S1A3A2925033)
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
disinformation campaigns, Twitter, 2012 South Korean presidential election, social bots, principal-agent model, election interference

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