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Political Astroturfing on Twitter: How to Coordinate a Disinformation Campaign
Open accessAbstract
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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“For Keller et al. (2020), another key characteristic of astroturfing is its reliance on centralized coordination, especially for disseminating and sharing information”
From Beyond Verification| Inauthentic Authenticity: Astroturfing to Generate True Affect Using Fakery (2026) · cites this paper as Keller et al., 2020
In the citing paper
“Astroturfing is most frequently equated with political or commercial communications strategy”
From Beyond Verification| Inauthentic Authenticity: Astroturfing to Generate True Affect Using Fakery (2026) · cites this paper as Keller et al., 2020
In the citing paper
“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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Lupovici, A. (2026) · Journal of International Relations and Development · doi:10.1057/s41268-026-00369-w · Cited by 3
“…campaigns stems from the challengers’ ability to take advantage of the anonymity of the cyber domain, misleading individuals Page 16 of 27 who consume social media content to believe that messages implemented and disseminated by challengers are authentic (Keller et al., 2020, 258–259).”
Chen, Q. (2026) · Online information review (Print) · doi:10.1108/oir-04-2025-0278 · Cited by 2
Just the tip of the iceberg? State of the art of coordinated social media manipulation research
Milzner, M., Thiele, D., & Gong, B. (2025) · Information Communication & Society · doi:10.1080/1369118x.2025.2596873 · Cited by 1
“Reflecting a principal– agent problem (Keller et al., 2020), principals delegate campaign implementation to agents: they commission the campaign.”
InfluentialThe Limits of Computational Propaganda: Investigating Underexplored Platforms and Contexts
Kermani, H., Neyazi, T. A., & Lecheler, S. K. (2025) · Political Communication · doi:10.1080/10584609.2025.2595596 · Cited by 4
“…substantially concentrates on such democratic contexts in other events or from a general perspective as well (Bennett & Livingston, 2018; Chomel et al., 2023; Ferrara, 2017; Hajli et al., 2022; Keller et al., 2020; Pierri et al., 2020; Rossetti & Zaman, 2023; Schoch et al., 2022; Starbird, 2019).”
A Compression-Based Approach to Detecting Automated and Coordinated Behavior on Social Media
Loru, E., Marco, N. D., Cinelli, M., & Quattrociocchi, W. (2025) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/3778356 · Cited by 4
“…to manipulate public opinion [35, 80, 100], provoke specific social responses [56, 87, 92], and orchestrate Information Operations (IOs) to amplify precise agendas [51, 99], thereby raising concerns about their potential role in the spreading of misinformation and propaganda [16, 28, 45, 86, 95].”
InfluentialHow Centralized is Party Communication on Social Media?
Swalve, T., Nyhuis, D., Hönnige, C., Huber, M., & Köker, P. (2025) · Social science computer review · doi:10.1177/08944393251399840 · Cited by 2
Muhle, F., & Bock, I. (2025) · Media and Communication · doi:10.17645/mac.10244 · Cited by 2
“…of artificial amplification that have been identified in the literature include the dissemination of particular content, e.g., via (co‐)retweet (Keller et al., 2020; Muhle, 2020), targeting popular users through mentions and replies (Shao et al., 2018), or misdirecting users to unrelated…”
Chen, Q., & Liu, Q. (2025) · Health Informatics Journal · doi:10.1177/14604582251381175 · Cited by 2
“Co-tweeting and co-retweeting networks were constructed using NetworkX, and Keller ’ s method 23 was applied to detect groups spreading the same tweet quickly.”
Hakami, Z., Feng, Y., & Cărbunar, B. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3757572 · Cited by 4
“With improvements in detection techniques [91, 104, 135, 154], recent research has turned toward understanding how IOs are experienced and resisted by different actors.”
How people perceived and engage with political astroturfing accounts
Limilia, P. (2025) · Communication Research and Practice · doi:10.1080/22041451.2025.2531637 · Cited by 3
Oliveira, G. S., Lobo, J. P., Venâncio, O. R., Vieira, V. D. F. V., Almeida, J. M., da Silva, A. P. C., Ferreira, R. S., & Ferreira, C. H. G. (2025) · Journal on Interactive Systems · doi:10.5753/jis.2025.5526 · Cited by 2
“Similarly, Keller et al .”
Transformative Media: A Critical Approach to Alt-right Media Appropriations
Jeppesen, S., Farokhi, Z., Ulthin, I. H., Faubert, E., Petersen, C. C., Hays, C., & Poole, K. M. (2025) · tripleC: Communication, Capitalism & Critique. Open Access Journal for a Global Sustainable Information Society · doi:10.31269/b3jpky66 · Cited by 2
“Consistent with repressive media’s commodity cooptation mechanism, astroturfing refers to top-down political or corporate Public Relations (PR) campaigns styled as grassroots movements (Keller et al. 2020).”
Demir, G., Darıcı, S., Tamer, Z., Taydaş, O., & Pamucar, D. (2025) · Journal of Computational Social Science · doi:10.1007/s42001-025-00408-5 · Cited by 2
“Page 6 of 48 Disinformation can also manipulate political participation, affecting election outcomes and other forms of political behavior [26, 51].”
Analyzing Support for U.S. Presidential Candidates in Twitter Polls
Scarano, S., Vasudevan, V., Samory, M., Yang, J., & Grabowicz, P. A. (2024) · Journal of Quantitative Description Digital Media · doi:10.51685/jqd.2024.icwsm.4 · Cited by 1
“This suggests that there may be some degree of astroturfing, i.e., inauthentic user behavior, involved in political campaigning via social polls (Keller et al., 2020b).”
BackgroundSelf-citationAlloing, C. (2024) · Les Enjeux de l'information et de la communication · doi:10.3917/enic.hs13.0047 · Cited by 2
Tilton, S., & Agozzino, A. (2023) · Cogent Social Sciences · doi:10.1080/23311886.2023.2193440 · Cited by 2
“This rhetorical impact to the global audience is more than the hashtag (s) one uses to organize the narrative, but is part of limiting the effectiveness of disinformation campaigns through strategic media literacy (Daer et al., 2014; Huang, 2020; Keller et al., 2019).”
BackgroundDevotees on an Astroturf: Media, Politics, and Outrage in the Suicide of a Popular FilmStar
Akbar, S. Z., Sharma, A., Mishra, D., Mothilal, R. K., Negi, H., Nishal, S., Panda, A., & Pal, J. (2022) · The Compass · doi:10.1145/3530190.3534801 · Cited by 2
“First, there are those who engage in the aggressive speech and coordinate campaigns – these can be thought of as the principals in a principal-agent framing [51].”
BackgroundSlanted Narratives, Social Media, and Foreign Influence in Libya
Grossman, S., Lyon, N., Sizer, L., & Jonsson, K. (2022) · Journal of Quantitative Description Digital Media · doi:10.51685/jqd.2022.010 · Cited by 2
“These campaigns make it appear as if accounts are ordinary citizens speaking on their own volition (Keller et al., 2020).”
BackgroundAnalyzing Twitter Users' Behavior Before and After Contact by the Internet Research Agency
Dutta, U., Hanscom, R., Zhang, J. S., Han, R. O., Lehman, T., Lv, Q., & Mishra, S. (2020) · arXiv.org · doi:10.48550/arxiv.2008.01273 · Cited by 2
“While prior work has studied in great detail the behavior of the IRA bot accounts and techniques that they employed to spread misinformation [8, 9, 19, 22], based on a data set released by Twitter [29], much less work has examined the targets of the IRA bots, namely the overall Twitter user population.”
Global Perspectives of Digital Political CommunicationPreprint
Shahreza, M. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4817955 · Cited by 2
Отношение к власти как фактор восприятия политического троллинга в российских социальных медиа
Стукал, Д., & Shilina, A. N. (2022) · Полис Политические исследования · doi:10.17976/jpps/2022.04.14 · Cited by 4
Detecting Propaganda in Trending Twitter Topics in India—A Metric Driven Approach
Hari, K., Aravind, D., Singh, A., & Das, B. (2021) · doi:10.1007/978-981-33-4367-2_62 · Cited by 2
The physics of news, rumors, and opinions
Caldarelli, G., Artime, O., Fischetti, G., Guarino, S., Nowak, A. K., Saracco, F., Holme, P., & Domenico, M. D. (2026) · Physics Reports · doi:10.1016/j.physrep.2026.05.002 · Cited by 12
Actors of Disinformation: Issuers and Recipients of Hoaxes in the 2024 U.S. Presidential Election
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Algospeak, Hiding in the Open: The Trade-off Between Legible Meaning and Detection Avoidance
Fillies, J., Robertson, R., & Hancock, J. T. (2026) · arXiv.org · doi:10.48550/arxiv.2605.06619 · Cited by 1
“LLMs have been exploited for a range of malicious purposes, from phishing attacks [1] and misinformation [2] to politically motivated social botnets and astroturfing campaigns [3, 4].”
Carter, C. C., Page, S., Borowiecki, M., Kostygina, G., Emery, S. L., & Feng, M. (2026) · Journal of Medical Internet Research · doi:10.2196/83791 · Cited by 1
Kulichkina, A., Balluff, P., Righetti, N., & Waldherr, A. (2026) · EPJ Data Science · doi:10.1140/epjds/s13688-026-00637-2 · Cited by 2
Wu, Y., & Yu, J.-Q. (2026) · Social science computer review · doi:10.1177/08944393261427645 · Cited by 1
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Abdelnour, J., Grolleau, G., & Mzoughi, N. (2026) · Public Choice · doi:10.1007/s11127-026-01376-8 · Cited by 1
“For instance, such transaction costs can include paying for legal counsel, hiring public relations firms, funding lob - bying intermediaries, and investing in elaborate communication or organizational structures to mask their use of astroturf groups (see Keller et al. 2020).”
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“Further, F. B. Keller et al. ( 2020 ) warned about the increased overall prevalence of disinformation on social media stating, “general trust in online discussion venues and their potential for political discourses will further erode” (p. 275).”
Pérez, R. C., Tejedor, S., Romero-Rodríguez, L. M., & Paucar-Villacorta, D. (2025) · Revista Latina de Comunicación Social · doi:10.4185/rlcs-2026-2553 · Cited by 1
Park, C. S., & Molla, M. A. M. (2025) · Howard Journal of Communications · doi:10.1080/10646175.2025.2587082 · Cited by 2
“The presence of bots and coordinated bot farms, which can artificially inflate visibility and steer emotional engagement toward polarizing or ideologically extreme content (Keller et al., 2020).”
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“The intention of disinfor-mation is most often to manipulate (Benkler et al., 2018), to harm (Wardle & Derakh-shan, 2017), or to gain some advantage, such as money (Herasimenka et al., 2023) or political influence (Keller et al., 2020).”
Gabor, E., Oancea, M., & Pripp, V. C. M. (2025) · Proceedings of the ... International Conference on Business Excellence · doi:10.2478/picbe-2025-0138 · Cited by 1
“Astroturfing is part of disinformation efforts not because of the transmitted message, which can illustrate the truth, but due to the fact that it generates “the false impression of independent popular support” (Keller, Schoch, Stier, & Yang, 2019, p.2).”
Yang, A. (2025) · The Information Society · doi:10.1080/01972243.2025.2498507 · Cited by 1
Ricard, J., Yañez, I., & Hora, L. (2025) · arXiv.org · doi:10.48550/arxiv.2504.12537 · Cited by 1
“- Disinformation spread during elections to weaken political rivals, as seen in the 2016 U.S. presidential election and 2012 South Korean election (Gunther et al., 2019; Keller et al., 2020).”
InfluentialParadowski, R. (2025) · The Copernicus Journal of Political Studies · doi:10.12775/cjps.2023/2024.003 · Cited by 1
“( Bastos & Farkas, 2019; Colliver et al ., 2018; Gruzd & Mai, 2020; Johnson et al ., 2017; Keller et al ., 2019; Watanabe, 2018) .”
Risca, N., Alamsyah, Abdillah, A., Hafiyah, N., Sonni, A., & Sisca, E. N. (2025) · MEDIAKITA · doi:10.30762/mediakita.v9i1.2744 · Cited by 1
“While this practice can potentially have a significant impact, it is difficult to assess its effectiveness without accurate information regarding the identity of the perpetrators (Keller et al., 2020).”
Discourses on smoke-free policies on Dutch Twitter: A social network analysis
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“These bots are often used for purposes such as spreading disinformation (Keller et al. 2020; Ruths 2019; Shao et al. 2018), in fl uencing elections (Bessi and Ferrara 2016; Buccoliero et al. 2020; Ferrara 2017; Scha ̈ fer, Evert, and Heinrich 2017), and distorting public opinion (Badawy, Ferrara,…”
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BackgroundSelf-citationI’d Rather Bite My Tongue Off Than Stand with Them: Paralysis of Political Engagement in Serbia
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“…most polluted, in the world” (Petrović 2018, 20), the pervasiveness of this technique of digital manipulation of the public, and the lack of trust it carries certainly contribute to the further polarization of the public (Keller et al. 2019), increasing the public’s reticence to engage in politics.”
BackgroundNetworks and Influencers in Online Propaganda Events: A Comparative Study of Three Cases in India
Sen, A., De, S., & Pal, J. (2024) · Proc. ACM Hum. Comput. Interact. · doi:10.1145/3653709 · Cited by 1
“Several previous works have touched upon the topic of astroturfing in various events and forms [43, 53, 85].”
BackgroundInteligencia artificial en los procesos electorales. ¿Qué podemos esperar de ChatGPT?
Icaza, G. D., & Garzón-Sherdek, K. (2023) · Revista Elecciones · doi:10.53557/elecciones.2023.v22n26.07 · Cited by 1
“No obstante, a pesar de que los chatbots se utilizan para verificar información (Morrish 2023), también pueden generar noticias falsas y desinformación mediante información sesgada o incompleta (Keller et al .”
BackgroundA Twitter Dataset for Pakistani Political Discourse
Haq, E.-U., Zia, H. B., Mogavi, R. H., Tyson, G., Lu, Y. K., Braud, T., & Hui, P. (2023) · arXiv.org · doi:10.48550/arxiv.2301.06316 · Cited by 1
“The ease of social media content generation and consumption leaves a common social media user susceptible to disinformation and astroturfing campaings [23] Given the anecdotes of using social media for astroturfing and disinformation within the country, this dataset can help identify such practices, and also methods t…”
BackgroundEvading the Public Eye: On Astroturfing in Open Aviation Data
Strohmeier, M., Olive, X., & Sun, J. (2022) · OpenSky · doi:10.3390/engproc2022028007 · Cited by 1
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dos Santos, M. D. (2022) · Revista FAMECOS · doi:10.15448/1980-3729.2022.1.42803 · Cited by 1
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Anzera, G., & Massa, A. (2021) · Wiley eBooks · doi:10.1002/9781119743347.ch3 · Cited by 7
López-Fierro, S., Chiriboga-Calderón, C., & Pacheco-Villamar, R. (2021) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata52589.2021.9671864 · Cited by 5
“1Within the political context, online astroturfing implies the distribution of a specific agenda via the Internet, through coordinated campaigns [11], which aim to influence electoral results [10].”
BackgroundThe Cocreational View of Character Assassination
Samiolenko, S. A. (2021) · doi:10.1002/9781118857205.ch6 · Cited by 1
Yang, A. (2024) · Hawaii International Conference on System Sciences · doi:10.24251/hicss.2024.341 · Cited by 1
BERT, GPT-3, Timnit Gebru et nous
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Beyond Verification| Inauthentic Authenticity: Astroturfing to Generate True Affect Using Fakery
Alloing, C., Fournier, V., Reid, V., Germain, S., Turbide, O., & Yates, S. (2026) · International Journal of Communication · doi:10.65476/qd17zh66
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Iannucci, L., Matakos, A., & Kivelä, M. (2026) · doi:10.48550/arxiv.2610.37970
“A few studies test suspicious accounts against control accounts [Pantè et al., 2025, Mungari et al., 2026], or compare the coordination of accounts in an information operation with samples of regular users [Keller et al., 2020].”
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Mustafa, H., Luczak–Roesch, M., & Johnstone, D. (2026) · Journal of Computational Social Science · doi:10.1007/s42001-026-00502-2 · Cited by 1
“[1, 34–37].”
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Kermani, H., Oudlajani, F., Yarahmadi, P., Soltani, H. M., Makki, M., & HosseiniKhoo, Z. (2026) · Democratization · doi:10.1080/13510347.2026.2733601
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Hsu, C.-Y., Ku, L.-W., & Chen, C.-C. (2026) · doi:10.48550/arxiv.2610.17723
“…of opinion is itself part of the mechanism— those who read themselves as a minority withdraw (Noelle-Neumann, 1974)—which is what coordinated campaigns manufacture, and why they are detected through account co-activity rather than post content (Keller et al., 2020; Schoch et al., 2022).”
The Threads that Fray: Wedge strategies and Chinese influence operations in the Indo-Pacific
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Almakaty, S. S. (2026) · Journalism and Media · doi:10.3390/journalmedia7040203 · Cited by 1
“Detecting coordinated manipulation within this environment increasingly depends on network methods capable of surfacing inauthentic coordination, from astroturfing operations to coordinated link-sharing communities (Giglietto et al., 2020; Keller et al., 2020).”
Information Operations Exploit APIs to Manipulate Social Media
Pote, M., Flammini, A., & Menczer, F. (2026) · doi:10.48550/arxiv.2610.02591
“Keller et al. [17], Schoch et al. [26] demonstrated that coordinated activity is often used to simulate grassroots support, a tactic known as astroturfing.”
Automated Influence: How Social Bots Reshape Discursive Opportunities in Online Activism
Li, L., & Margetts, H. (2026) · Social Media + Society · doi:10.1177/20563051261490338
Rethinking the Concept of Publics in Public Relations in the Age of Artificial Intelligence
Güler, Ö. R. (2026) · Dynamics in Social Sciences and Humanities · doi:10.62425/dssh.2012478
How Artificial Intelligence Shapes Human Narratives
Priniski, J. H. (2026) · Journal of Language and Social Psychology · doi:10.1177/0261927x261493082
Ichikawa, K., SUGANO, B. T., Toya, G., Wu, Q., Hashimoto, Y., Toyoda, M., Yoshinaga, N., & Sasahara, K. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2610.00305
“There is also work that combines these elements Keller et al. [2020].”
Fayezi, S. (2026) · Journal of Management & Governance · doi:10.1007/s10997-026-09811-0
Marco, N. D., Cinelli, M., Nakano, S., & Frosini, A. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2609.24398
Examining the Patterns of Algorithmic Amplification in the Context of Political Astroturfing
S., S. (2026) · International Journal of Innovative Science and Research Technology · doi:10.38124/ijisrt/26sep336
“Keller, Schoch, Stier, and Yang (2019) systematically identified how the political astroturfing accounts on Twitter through a coordinated network simulate genuine, mobilized support for political favor.”
AI-Facilitated Astroturfing in Medical Tourism: Evidence from YouTube Comment Sections
Karimova, G. Z., & Rasool, S. (2026) · Journal of Global Marketing · doi:10.1080/08911762.2026.2717514
Kopanov, K., & Atanasova, T. V. (2026) · Information · doi:10.3390/info17080727
Tao, S., Zhao, Y., & Hong, T. (2026) · Systems · doi:10.3390/systems14070817
Yanes, N., Jitkajornwanich, K., Kee, K. F., & Perlmutter, D. D. (2026) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2026.2691175 · Cited by 2
“…technical limitations but the fundamental challenge of identifying intentional patterns in high-noise environments, a challenge that empirical research is only beginning to characterize (Keller et al., 2020; Schoch et al., 2022) and that PWAV is positioned to help address rather than fully resolve.”
Einarsson, H., Einarsson, H., Ólafsson, J. G., & Þorsteinsson, J. G. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2607.05217
“Astroturfing, coordinated campaigns posing as ordinary citizens, long predates these models (Keller et al., 2020), but generative AI removes its main bottleneck: the writing.”
García, J. G., & Magdaleno, M. I. A. (2026) · Online Information Review · doi:10.1108/oir-05-2025-0385
Tagging the Emirate: Language, Coordination and the Taliban's Digital Pursuit of Legitimacy
Oates, H. (2026) · Global Policy · doi:10.1111/1758-5899.70182
Lenk, T. (2026) · International Journal of Strategic Communication · doi:10.1080/1553118x.2026.2655654
James, D. A. (2026) · Journal of Technology in Human Services · doi:10.1080/15228835.2026.2674810 · Cited by 2
Emotion Impact and Contagion Mechanism of Misinformation: A Network‐Based Risk Analysis
Chen, Q. (2026) · Risk Analysis · doi:10.1111/risa.70265
Tactical Coordination Strategies of Pop-Culture Communities Under Automated Moderation
Luo, Z.-Y. (2026) · Interpretations and Perspectives · doi:10.70693/pfgef802
“Unlike bot-driven astroturfing (Keller et al., 2020), digital fan groups demonstrate unique, human-driven mobilization patterns based on a collective understanding of platform algorithms, often referred to as coordinated algorithmic action (CAA) (Zhang et al., 2024).”
Fang, W.-K., & Nie, C. (2026) · Information Research · doi:10.47989/ir31263122
“Researchers have focused on analysing bot behaviour and profiles (Confessore et al., 2018; Keller et al., 2020) while developing advanced detection tools to combat bots’ harmful influence (Ferrara, 2023; Nightingale and Farid, 2022).”
IO-X: Detecting and Attributing Content-Duplicating Influence Operations on X (Twitter)
Shafin, A. A., Siddique, M. N., & Carbunar, B. (2026) · The Web Conference · doi:10.1145/3774904.3792666
Kermani, H. (2026) · Journal of Information Technology & Politics · doi:10.1080/19331681.2026.2645613
Badade, A. B., & Dhanaraj, R. K. (2026) · International Conference on Emerging Smart Computing and Informatics (ESCI) · doi:10.1109/esci68015.2026.11493366 · Cited by 1
“One of the major processes is in the creation of perceived source credibility, in which the coordinated accounts attempt to simulate realistic ways of interacting with the public to create the illusion of agreement (Liu et al., 2020).”
Uzunoğlu, S. (2026) · Journalism Studies · doi:10.1080/1461670x.2026.2639080
“Seminal work by Keller et al. (2020) dissected a state-linked campaign in South Korea, revealing coordination signatures that betray underlying sponsorship, while studies from Mexico (Piña-García and Espinoza 2022) and analyses of corporate front-groups (Mix and Waldo 2015; Wear 2014) underscore…”
InfluentialLenk, T. (2026) · Humanities and Social Sciences Communications · doi:10.1057/s41599-026-06656-8
Digital delegitimization: Biden representations in the astroturfing discourse of the RuNet
Mukhambetova, K., Mikhailov, D., & Ternov, N. (2025) · Media, War & Conflict · doi:10.1177/17506352251403052
Tasențe, T., & Popescu, C.-D. (2025) · Revista ICONO 14. Revista científica de Comunicación y Tecnologías emergentes · doi:10.7195/ri14.v23i1.2278
“While detection methods have advanced - including network analysis, linguistic patterning, and bot detection - many campaigns blend real and fake elements in ways that circumvent automated systems (Chagas et al., 2022; Keller et al., 2020).”
InfluentialFake News and Its Influence on Political Polarization
Asthana, S. (2025) · South Sight: Journal of Media and Society Inquiry · doi:10.14710/southsight.202528925
“This includes coordinated networks of trolls and bots, as well as state-sponsored campaigns aimed at influencing election results (Keller et al., 2020);(Robles et al., 2022).”
García-Estévez, N., Ballesteros-Aguayo, L., & Ribeiro, J. C. (2025) · Revista de Comunicación · doi:10.26441/rc24.2-2025-3988
Kolaborasi CekFakta.com Hadapi Klaim Kompleks dan Disinformasi Debat Pemilu 2024
Permanasari, F. G., & Pabundu, D. D. (2025) · Jurnal Audience · doi:10.33633/ja.v8i2.12334
Black, C. A. (2025) · Quality & Quantity: International Journal of Methodology · doi:10.1007/s11135-025-02213-8
Debanath, K., Aich, S., & Srizon, A. Y. (2025) · 2025 2nd International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM) · doi:10.1109/ncim65934.2025.11160229
“Keller et al. [15] identified bot networks specifically targeting swing states, while Badawy et al. [16] revealed bots’ preference for amplifying extreme political content.”
Virality detection and control strategies in rumor models
Rifà, E., Vicens, J., & Cozzo, E. (2025) · doi:10.48550/arxiv.2505.24795
“In fact, previously proposed astroturfing detection methods rely on the analysis of interaction networks, linguistic content, and user metadata [4, 27], being computationally and data intensive, our results allow early detection methods based on the statistical analysis of the new spreader time…”
Transformative Medien: Alternative Medien rutschen von links nach rechts
Jeppesen, S., ulthiin, I., Farokhi, Z., Faubert, E., Poole, K. M., Hays, C., & Petersen, C. (2025) · Forschungsjournal Soziale Bewegungen · doi:10.1515/fjsb-2025-2006
Astroturfing Exposed: Uncovering the Role of Astroturfing in Shaping Trust and Engagement Online
Badade, A. B., & Dhanaraj, K. (2024) · 2024 International Conference on Computing and Intelligent Reality Technologies (ICCIRT) · doi:10.1109/iccirt59484.2024.10921987
“…and it proves that interaction analysis does precisely identify astroturfing behavior Political Astroturfing on Twitter: How to Coordinate a Disinformation Campaign (2020), [6]; this article uses network analysis of Twitter data related to political campaigns to detect misinformation clusters.”
Social bots sour activist sentiment without eroding engagement
Li, L., Vásárhelyi, O., & Vedres, B. (2024) · arXiv.org · doi:10.48550/arxiv.2403.12904
“These automated accounts are specifically designed to participate in political discussions [2], leading us to analyze users interacting with astroturfs separately from those who interacted with non-astroturfs.”
Background
Metadata
- 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
- Publisher
- Informa UK Limited
- 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
- green
- hdl.handle.net
- 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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