The DOI matches its Crossref record; 35 of the 46 references it cites were found in a registry or an index.
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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In the citing paper
“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
Citations
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Cited by
Sorted by citations
Social Media and Fake News in the 2016 Election
Allcott, H., & Gentzkow, M. (2017) · Journal of Economic Perspectives · doi:10.1257/jep.31.2.211 · Cited by 6,767
Susceptibility to misinformation about COVID-19 around the world
Roozenbeek, J., Schneider, C. R., Dryhurst, S., Kerr, J., Freeman, A. L. J., Recchia, G., van der Bles, A. M., & van der Linden, S. (2020) · Royal Society Open Science · doi:10.1098/rsos.201199 · Cited by 1,447
Fake news detection: A hybrid CNN-RNN based deep learning approach
Nasir, J. A., Khan, O. S., & Varlamis, I. (2021) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2020.100007 · Cited by 568
Earl, J. (2022) · Science Advances · doi:10.1126/sciadv.abl8198 · Cited by 250
“These messages drew attention away from negative news, denigrated the opposition, and raised divisive issues ( 164 ).”
BackgroundThe False positive problem of automatic bot detection in social science research
Rauchfleisch, A., & Kaiser, J. (2020) · PLOS ONE · doi:10.1371/journal.pone.0241045 · Cited by 184
“Overall it is also important to broaden the perspective and focus more on political digital astroturfing [46] for which bots are just one potential dimension [47].”
BackgroundUncovering Coordinated Networks on Social Media: Methods and Case Studies
Pacheco, D., Hui, P.-M., Torres-Lugo, C., Truong, B. T., Flammini, A., & Menczer, F. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v15i1.18075 · Cited by 140
Giglietto, F., Righetti, N., Rossi, L., & Marino, G. (2020) · Information Communication & Society · doi:10.1080/1369118x.2020.1739732 · Cited by 193
“shifting the focus from content to dynamics of information spreading within online networks (Hui et al., 2019; Keller et al., 2019).”
BackgroundBotometer 101: social bot practicum for computational social scientists
Yang, K.-C., Ferrara, E., & Menczer, F. (2022) · Journal of Computational Social Science · doi:10.1007/s42001-022-00177-5 · Cited by 159
“They may simply generate a large volume of posts to amplify certain narratives [21, 26] or to manipulate the price of stocks [24, 25] and cryptocurrencies [23].”
BackgroundBreaking Harmony Square: A game that “inoculates” against political misinformation
Roozenbeek, J., & van der Linden, S. (2020) · Harvard Kennedy School Misinformation Review · doi:10.37016/mr-2020-47 · Cited by 171
“, 2017), for example, by fueling outgroup hostility, a critical element of both organic misinformation and targeted disinformation campaigns, particularly during contentious political events such as the 2020 US Presidential elections (Groshek & Koc-Michalska, 2017; Hindman & Barash, 2018; Iyengar & Massey, 2018; Kelle…”
BackgroundCross-Platform Disinformation Campaigns: Lessons Learned and Next Steps
Starbird, K., & Wilson, T. (2020) · Harvard Kennedy School Misinformation Review · doi:10.37016/mr-2020-002 · Cited by 123
“…to focus on activities on a single social media platform such as Twitter (e.g. Arif et al., 2018; Broniatowski et al., 2018; Wilson et al., 2018, Keller et al., 2019; Zannettou et al., 2019), or YouTube (e.g. Hussain et al., 2018), or in the surrounding news media ecosystem (e.g. Starbird,…”
BackgroundHameleers, M. (2022) · Communication Theory · doi:10.1093/ct/qtac021 · Cited by 158
“…is astroturfing: Coordinated campaigns 4 Disinformation as a context-bound phenomenon that employ real people to present certain beliefs, identities or interpretations imitating grassroot movements that signal widespread social support for these beliefs (Keller et al., 2020; Zhang et al., 2013).”
Do social media undermine social cohesion? A critical review
González‐Bailón, S., & Yphtach Lelkes, B. (2022) · Social Issues and Policy Review · doi:10.1111/sipr.12091 · Cited by 143
Zerback, T., Töpfl, F., & Knöpfle, M. (2020) · New Media & Society · doi:10.1177/1461444820908530 · Cited by 105
“So far, however, this research has focused almost exclusively on how to identify fake accounts or automated social bots (Keller et al., 2019; King et al., 2017).”
BackgroundDo large language models have a legal duty to tell the truth?
Wachter, S., Mittelstadt, B., & Russell, C. (2024) · Royal Society Open Science · doi:10.1098/rsos.240197 · Cited by 104
“109 Two points are important to note.”
BackgroundUnveiling Coordinated Groups Behind White Helmets Disinformation
Pacheco, D. F., Flammini, A., & Menczer, F. (2020) · International World Wide Web Conference (WWW) · doi:10.1145/3366424.3385775 · Cited by 81
The Routledge Companion to Media Disinformation and Populism
Hameleers, M. M. T. L., de Vreese, C. H., Tumber, H., & Waisbord, S. (2021) · Routledge eBooks · doi:10.4324/9781003004431 · Cited by 140
A Survey on the Use of Large Language Models (LLMs) in Fake News
Papageorgiou, E., Chronis, C., Varlamis, I., & Himeur, Y. (2024) · Future Internet · doi:10.3390/fi16080298 · Cited by 80
Uncovering the Truth about Fake News: A Research Model Grounded in Multi-Disciplinary Literature
George, J. J., Gerhart, N., & Torres, R. (2021) · Journal of Management Information Systems · doi:10.1080/07421222.2021.1990608 · Cited by 93
Amplifying influence through coordinated behaviour in social networks
Weber, D., & Neumann, F. (2021) · Social Network Analysis and Mining · doi:10.1007/s13278-021-00815-2 · Cited by 82
“Supporting criteria relying on interactions alone, as observed in the literature (Ratkiewicz et al. 2011; Keller et al. 2019), include retweeting the same tweet ( co-retweet ), using the same hashtags ( co-hashtag ) or URLs ( co-URL ), or mentioning the same accounts ( co-mention ).”
BackgroundMethodInfluentialComputational Social Science and the Study of Political Communication
Theocharis, Y., & Jungherr, A. M. (2020) · Political Communication · doi:10.1080/10584609.2020.1833121 · Cited by 106
“While methods of labeling social media accounts as bots abound (Varol et al., 2017), findings have been mixed (Keller et al., 2020).”
MethodCoordinated Behavior on Social Media in 2019 UK General Election
Nizzoli, L., Tardelli, S., Avvenuti, M., Cresci, S., & Tesconi, M. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v15i1.18074 · Cited by 95
“Also Assenmacher et al. propose a 2-step framework for detecting IOs (Assenmacher et al. 2020b; 2020a).”
BackgroundInfluentialContent-based features predict social media influence operations
Alizadeh, M., Shapiro, J. N., Buntain, C., & Tucker, J. A. (2020) · Science Advances · doi:10.1126/sciadv.abb5824 · Cited by 90
“A small body of work has shown that it is possible to find coordinated influence efforts on social media using unsupervised ( 4 , 20 ) or supervised machine learning ( 21 , 22 ).”
On the Detection of Disinformation Campaign Activity with Network Analysis
Vargas, L., Emami, P., & Traynor, P. (2020) · Proceedings of the 2020 ACM SIGSAC Conference on Cloud Computing Security Workshop · doi:10.1145/3411495.3421363 · Cited by 74
“Other recent developments in the automatic extraction of Twitter communities likely to be engaged in astroturfing campaigns have mainly focused on tweet coordination networks [11, 12, 17], text-based analysis [11], and specific temporal patterns [17].”
BackgroundMethodInfluentialAnatomy of an AI-powered malicious social botnet
Yang, K., & Menczer, F. (2024) · Journal of Quantitative Description: Digital Media · doi:10.51685/jqd.2024.icwsm.7 · Cited by 71
“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).”
BackgroundInfluentialPietro, R. D., Raponi, S., Caprolu, M., & Cresci, S. (2020) · Advances in information security · doi:10.1007/978-3-030-60618-3_2 · Cited by 4
Supersharers of fake news on Twitter
Baribi-Bartov, S., Swire‐Thompson, B., & Grinberg, N. (2024) · Science · doi:10.1126/science.adl4435 · Cited by 81
An analysis of AstraZeneca COVID-19 vaccine misinformation and fear mongering on Twitter
Jemielniak, D., & Krempovych, Y. (2021) · Public Health · doi:10.1016/j.puhe.2021.08.019 · Cited by 77
Haupt, M. R., Jinich‐Diamant, A., Li, J., Nali, M. C., & Mackey, T. K. (2020) · Online Social Networks and Media · doi:10.1016/j.osnem.2020.100114 · Cited by 61
Disinformation on digital media platforms: A market-shaping approach
Ruiz, C. A. D. (2023) · New Media & Society · doi:10.1177/14614448231207644 · Cited by 97
Retweeting for COVID-19: Consensus building, information sharing, dissent, and lockdown life
Thelwall, M., & Thelwall, S. (2020) · arXiv.org · doi:10.48550/arxiv.2004.02793 · Cited by 58
Duan, Z., Li, J., Lukito, J., Yang, K.-C., Chen, F., Shah, D. V., & Yang, S. (2022) · Human Communication Research · doi:10.1093/hcr/hqac012 · Cited by 66
“An emerging line of scholarship has only begun to compare the keywords (Keller et al., 2020) and sentiments (Bessi & Ferrara, 2016) posted by human-like and bot-like accounts.”
Coordination patterns reveal online political astroturfing across the world
Schoch, D., Keller, F. B., Stier, S., & Yang, J. (2022) · Scientific Reports · doi:10.1038/s41598-022-08404-9 · Cited by 64
Self-citationAssessing Language Model Deployment with Risk CardsPreprint
Derczynski, L., Kirk, H. R., Balachandran, V., Kumar, S., Tsvetkov, Y., Leiser, M. R., & Mohammad, S. M. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2303.18190 · Cited by 53
“Other text requires situational context for harm risk to manifest: for example, authoring many fake comments evincing a certain view and posting of them online as genuine, in an astroturfing effort [15].”
BackgroundDisinformation, social media, bots, and astroturfing: the fourth wave of digital democracy
García-Orosa, B. (2021) · El Profesional de la información · doi:10.3145/epi.2021.nov.03 · Cited by 80
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Online astroturfing: A problem beyond disinformation
Chan, J. (2022) · Philosophy & Social Criticism · doi:10.1177/01914537221108467 · Cited by 49
“What astroturfers do is sow distrust and instigate arguments on such online social platforms, creating uncertainty, and disrupting genuine communication (Keller et al. 2019).”
BackgroundSpotting Political Social Bots in Twitter: A Use Case of the 2019 Spanish General Election
Pastor-Galindo, J., Zago, M., Nespoli, P., Bernal, S. L., Celdrán, A., Pérez, M., Ruipérez-Valiente, J. A., Pérez, G., & Mármol, F. G. (2020) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2020.3031573 · Cited by 48
“grassroot participation while being secretly orchestrated and funded [12].”
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Neyazi, T. A., Kalogeropoulos, A., & Nielsen, R. (2021) · Social Media + Society · doi:10.1177/20563051211009013 · Cited by 46
“While there has been a growing use of the term “fake news,” academics have raised concerns about this umbrella term because of its conceptual ambiguity and misuse by political actors (Keller et al., 2020).”
BackgroundNFTDisk: Visual Detection of Wash Trading in NFT Markets
Wen, X.-L., Wang, Y., Yue, X., Zhu, F., & Zhu, M. (2023) · International Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581466 · Cited by 44
“One possible application of NFTDisk can be the identification and analysis of political astroturfing on Twitter [22, 47], where a group of Twitter accounts are manipulated by their employer to distribute disinformation in a coordinated manner.”
BackgroundInfluential“I agree with you, bot!” How users (dis)engage with social bots on Twitter
Wischnewski, M., Ngo, T., Bernemann, R., Jansen, M., & Krämer, N. C. (2022) · New Media & Society · doi:10.1177/14614448211072307 · Cited by 46
“Previous studies could show that social bots can amplify specific content, leading to “megaphone effects” (Woolley and Guilbeault, 2019: 193), as well as initiating political astroturfing campaigns (Keller et al., 2020).”
BackgroundTrend Alert: A Cross-Platform Organization Manipulated Twitter Trends in the Indian General Election
Jakesch, M., Garimella, K., Eckles, D., & Naaman, M. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479523 · Cited by 57
Giglietto, F., Righetti, N., Rossi, L., & Marino, G. (2020) · International Conference on Social Media and Society (SMSociety) · doi:10.1145/3400806.3400817 · Cited by 40
“From that moment on, it became clear that the antagonist online participatory practices of sharing, collaborating and organizing collective actions [29, 44], which used to be considered the prerogative of democratizing forces fighting established and sometimes oppressive powers, could be just as…”
BackgroundThe Pervasive Presence of Chinese Government Content on Douyin Trending VideosPreprint
Lu, Y., & Pan, J. (2021) · Social Science Research Network · doi:10.2139/ssrn.3794898 · Cited by 38
“The first is by using bots, trolls, computational propaganda, and other inauthentic and often deceptive means to fabricate the appearance of support and interest (Bjola, 2017; Keller et al., 2020; King et al., 2017; Marwick & Lewis, 2017; Sanovich, 2017; Woolley & Howard, 2017).”
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“…the same year, Bolsonaro’s spreading of disinforma-tion messages via WhatsApp during the 2018 Brazilian presidential election, and more recently, Milei’s social media campaign in the 2023 Argentinian elections )Keller et al., 2020; Howard & Kollanyi, 2016; Santini et al., 2021; Swire et al., 2017(.”
Weaponizing narrative: Russia contesting EUrope’s liberal identity, power and hegemony
Tyushka, A. (2021) · Journal of Contemporary European Studies · doi:10.1080/14782804.2021.1883561 · Cited by 50
“…instance, the financing of the EU’s radical right and left parties (thus investing in the proxied antagonization of an adversary’s political and discursive fields) or subverting the very domestic debate via social media ‘astroturfing’ campaigns (Tyushka 2019: 12; Keller et al. 2020; Kayali 2020).”
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“Astroturfing is a subcategory of disinformation, defined as having a purposeful, and often malicious, intent to deliberately mislead audiences in support of strategic objectives (Keller, Schoch, Stier, & Yang, 2019).”
BackgroundInfluentialPatterns of linguistic simplification on social media platforms over time
Marco, N. D., Loru, E., Bonetti, A., Serra, A. O. G., Cinelli, M., & Quattrociocchi, W. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2412105121 · Cited by 48
A Survey on the Use of Graph Convolutional Networks for Combating Fake News
Varlamis, I., Michail, D., Glykou, F., & Tsantilas, P. (2022) · Future Internet · doi:10.3390/fi14030070 · Cited by 35
“The literature behind disinformation campaigns on Twitter is long [4,13–15] and keeps growing when new election campaigns occur around the globe or when crypto-currency and stock investors want to influence the market through social media [16–19].”
BackgroundHackenburg, K., Ibrahim, L., Tappin, B. M., & Manos Tsakiris, A. (2025) · AI & Society · doi:10.1007/s00146-025-02464-x · Cited by 44
“Here, we use the largest publicly accessible LLM to date, GPT-4, to ask two related questions:”
Ready-to-(ab)use: From fake account trafficking to coordinated inauthentic behavior on Twitter
Mazza, M., Cola, G., & Tesconi, M. (2022) · Online Social Networks and Media · doi:10.1016/j.osnem.2022.100224 · Cited by 36
New Dimensions of Information Warfare
Pietro, R. D., Raponi, S., Caprolu, M., & Cresci, S. (2020) · Advances in information security · doi:10.1007/978-3-030-60618-3 · Cited by 53
“Predictably, political astroturfing has the potential to heavily influence electoral outcomes, as well as any other forms of political behavior [130].”
BackgroundDetection and Characterization of Coordinated Online Behavior: A Survey
Mannocci, L., Mazza, M., Monreale, A., Tesconi, M., & Cresci, S. (2026) · ACM Computing Surveys · doi:10.1145/3839225 · Cited by 39
“Methods based on fixed similarity thresholds discard all edges in the network whose weight 𝑤 𝑤 th , and all the resulting disconnected nodes [12–14, 16, 17, 19–21, 23, 28, 29, 38–41, 46, 49, 54, 56–59, 67, 68, 78, 87–89, 91– 93, 95, 96, 99, 100, 102, 112, 116, 135, 138, 142, 145, 149].”
InfluentialDistract and Divert: How World Leaders Use Social Media During Contentious Politics
Barberá, P., Gohdes, A., Iakhnis, E., & Zeitzoff, T. (2022) · The International Journal of Press/Politics · doi:10.1177/19401612221102030 · Cited by 39
Memetic persuasion and WhatsAppification in Indonesia’s 2019 presidential election
Baulch, E., Matamoros-Fernández, A., & Suwana, F. (2022) · New Media & Society · doi:10.1177/14614448221088274 · Cited by 25
“In this way, campaign team staff, often on party pay-rolls, are able to assume the guise of everyday or ‘grassroots’ users to shape public discourse on WhatsApp, in a manner that resembles ‘astroturfing’ (see Johns and Cheong, 2019; Keller et al., 2020).”
BackgroundTactics, Threats & Targets: Modeling Disinformation and its Mitigation
Mirza, S., Begum, L., Niu, L., Pardo, S., Abouzied, A., Papotti, P., & Pöpper, C. (2023) · Network and Distributed System Security Symposium · doi:10.14722/ndss.2023.23657 · Cited by 30
“counterfeit::astroturfing Astroturfing as a tactic aims to create an illusion of a genuine grass-roots support or opposition to a group or a policy, through centrally-coordinated witting agents that appear to be independent and ordinary citizens (n = 3) [54].”
BackgroundZerback, T., & Toepfl, F. (2021) · Political Psychology · doi:10.1111/pops.12767 · Cited by 34
Coordinated Behavior in Information Operations on Twitter
Cima, L., Mannocci, L., Avvenuti, M., Tesconi, M., & Cresci, S. (2024) · IEEE Access · doi:10.1109/access.2024.3393482 · Cited by 23
“Other detection techniques analyze network structures with the goal of identifying groups of users that are involved in an IO [3], [10], [19], [20], and to estimate their influence on the rest of the network [33].”
BackgroundMethodInfluentialGraham, T., Hames, S., & Alpert, E. (2024) · Journal of Computational Social Science · doi:10.1007/s42001-024-00260-z · Cited by 21
“The Coordination Network Toolkit 1 includes functionality for co-tweeting and co-retweeting [8, 9], where accounts post exactly the same text (co-tweets) or repost the same post within a short time window (co-retweets).”
InfluentialDaume, S., Galaz, V., & Bjersér, P. (2023) · Social Media + Society · doi:10.1177/20563051231168370 · Cited by 32
“…element of account automation as well as the likelihood that an account is employed as part of an astroturf campaign, that is, is part of a group of coordinated accounts with the intent to give the impression of an organically emerging grassroots social media movement (F. B. Keller et al., 2020).”
BackgroundLiang, F., & Lu, S.-N. (2023) · Social Media + Society · doi:10.1177/20563051231177946 · Cited by 25
“Both could be used in online astroturfing, referring to the attempts that create an impression of widespread grassroots support for a policy, a cause, or a stance, where little such support exists (Keller et al., 2020).”
BackgroundSmart, B., Watt, J., Benedetti, S., Mitchell, L., & Roughan, M. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19097-1_3 · Cited by 42
“We will examine coordination campaigns and coordination networks [34,12,27,14,19] to quantify the impact of coordinated activity in the social network structure and to further investigate its influence on social media users.”
Automation on Twitter: Measuring the Effectiveness of Approaches to Bot Detection
Beatson, O., Gibson, R., Cantijoch, M., & Elliot, M. J. (2021) · Social Science Computer Review · doi:10.1177/08944393211034991 · Cited by 22
Exposure to social bots amplifies perceptual biases and regulation propensity
Yan, H. Y., Yang, K.-C., Shanahan, J. E., & Menczer, F. (2023) · Scientific Reports · doi:10.1038/s41598-023-46630-x · Cited by 24
“…disseminate fake news 3 and inflammatory information 4,5 , exploit the private information of users 6 , sway public attention on controversial topics 7–9 , and create false public support for political and commercial gain 1,10,11 , especially during major political events such as elections 12–14 .”
BackgroundLindquist, J. A., & Weltevrede, E. (2024) · Social Media + Society · doi:10.1177/20563051231224721 · Cited by 25
Guardians of truth? Fact-checking the ‘disinfodemic’ in Southern Africa during the COVID-19 pandemic
Mare, A., & Munoriyarwa, A. (2022) · Journal of African Media Studies · doi:10.1386/jams_00065_1 · Cited by 25
A language framework for modeling social media account behavior
Nwala, A. C., Flammini, A., & Menczer, F. (2023) · EPJ Data Science · doi:10.1140/epjds/s13688-023-00410-9 · Cited by 31
Platforms, Politics, and the Crisis of Democracy: Connective Action and the Rise of Illiberalism
Bennett, W. L., & Livingston, S. G. (2025) · Perspectives on Politics · doi:10.1017/s1537592724002123 · Cited by 43
“…domestic operators use trolls, bots, and sock puppets as super-spreaders of disin-formation on social media platforms (Ahmad et al. 2019; Bradshaw and Howard 2019; Jamieson 2020; Keller et al. 2019; Linvill and Warren 2020; Weissmann et al. 2021; Woolley and Guilbeault 2017; Zannettou et al. 2019).”
MeVer NetworkX: Network Analysis and Visualization for Tracing Disinformation
Papadopoulou, O., Makedas, T., Apostolidis, L., Poldi, F., Papadopoulos, S., & Kompatsiaris, Y. (2022) · Future Internet · doi:10.3390/fi14050147 · Cited by 21
Pilot Study Suggests Online Media Literacy Programming Reduces Belief in False News in Indonesia
Thomas, P. B., Hogan-Taylor, C., Yankoski, M., & Weninger, T. (2021) · First Monday · doi:10.5210/fm.v27i1.11683 · Cited by 21
“While the use of targeted misinformation campaigns by state actors is well documented (Keller et al. 2020, Zannettou et al. 2019, Bradshaw & Howard 2018), ordinary citizens often both consume and spread (mis)information through their well-meaning online activity, which can inadvertently help to…”
BackgroundDarius, P. (2022) · Social Network Analysis and Mining · doi:10.1007/s13278-022-00958-w · Cited by 22
Examining characteristics of prebunking strategies to overcome PR disinformation attacks
Boman, C. D. (2021) · Public Relations Review · doi:10.1016/j.pubrev.2021.102105 · Cited by 28
“These campaigns work to intentionally spread harmful or inaccurate disin-formation, which can be particularly troubling for organizations on the receiving end of an attack (Cho et al., 2011; Keller et al., 2020).”
BackgroundInauthentic Newsfeeds and Agenda Setting in a Coordinated Inauthentic Information Operation
Ehrett, C., Linvill, D. L., Smith, D. H., Warren, P. L., Bellamy, L., Moawad, M., Moran, O., & Moody, M. (2021) · Social Science Computer Review · doi:10.1177/08944393211019951 · Cited by 34
“They did not focus messaging on key dates (Keller, et al., 2020; King et al., 2017); instead, they posted quite regularly, almost mechanically.”
BackgroundLiquid Disinformation Tactics: Overcoming Social Media Countermeasures through Misleading Content
Ferreira, R. R. (2021) · Journalism Practice · doi:10.1080/17512786.2021.1914707 · Cited by 13
“Keller et al. (2020) established that the South Korean government created and controlled a network of Twitter accounts to gen-”
BackgroundBehavior-Based Machine Learning Approaches to Identify State-Sponsored Trolls on Twitter
Alhazbi, S. (2020) · IEEE Access · doi:10.1109/access.2020.3033666 · Cited by 17
“Our work is based on the concept that the behavior of sponsored-trolls on social media is mainly driven by extrinsic motivations [23], this is completely different from the behavior of genuine users whose online political participation is driven by intrinsic motivations relating to self-efficacy and…”
BackgroundInfluentialLabeled Datasets for Research on Information Operations
Seckin, O. C., Pote, M., Nwala, A. C., Yin, L., Luceri, L., Flammini, A., & Menczer, F. (2024) · International Conference on Web and Social Media · doi:10.48550/arxiv.2411.10609 · Cited by 19
“One of the first documented IOs was uncovered in a South Korean social media platform in 2012 (Keller et al. 2020).”
Cazzamatta, R. (2024) · New Media & Society · doi:10.1177/14614448241268896 · Cited by 19
“Inauthentic behaviors (Keller et al., 2020) such as creating fake accounts, using bots to artificially boost engagement metrics (Chan, 2024; Tucker et al., 2018), or manipulating online discussions through coordinated efforts obscure the origins of falsehoods and worsen misinformation by…”
Analyzing Twitter Users' Behavior Before and After Contact by the Russia's Internet Research Agency
Dutta, U., Hanscom, R., Zhang, J. S., Han, R. Y., Lehman, T. S., Lv, Q., & Mishra, S. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449164 · Cited by 24
“e IRA campaign during the 2016 election has drawn great interest in the research community. Earlier research has characterized the strategies of IRA activity on social media from various perspectives [8, 9, 19, 22]. To the best of our knowledge, most of this work does not examine how IRA accounts interact with general…”
BackgroundMethodA Bibliometric Analysis of Disinformation through Social Media
Akram, M., Nasar, A., & Arshad-Ayaz, A. (2022) · Online Journal of Communication and Media Technologies · doi:10.30935/ojcmt/12545 · Cited by 18
Childs, M. C., Buntain, C., Trujillo, M. Z., & Horne, B. (2022) · Web Science Conference · doi:10.1145/3501247.3531571 · Cited by 18
“At the same time, we know that disinformation messages can also be amplified by bot accounts on Twitter [20, 36].”
BackgroundSuper-amplifiers! The role of Twitter extended party networks in political elections
Yoon, N., Hemsley, J., Smith, A., Simpson, E., & Eakins, J. (2022) · Policy & Internet · doi:10.1002/poi3.295 · Cited by 18
Orlando, G. M., Ye, J., Gatta, V. L., Saeedi, M., Moscato, V., Ferrara, E., & Luceri, L. (2026) · International World Wide Web Conference (WWW) · doi:10.1145/3774904.3792580 · Cited by 20
“Guided by these observations, we next present our research hypotheses and methodology.”
Bad actors never sleep: content manipulation on Reddit
Potter, M. (2021) · Continuum · doi:10.1080/10304312.2021.1983254 · Cited by 16
“Such coordinated and sustained disinformation campaigns in which participants pretend to be ordinary citizens acting independently, can influence electoral outcomes and other forms of political behaviour (Keller et al. 2020).”
BackgroundDetecting astroturf lobbying movements
Lits, B. (2020) · Communication and the Public · doi:10.1177/2057047320969435 · Cited by 36
“There is a growing body of literature devoted to the phenomenon, but few studies are suggesting methods to detect astroturf movements (Keller et al., 2019).”
BackgroundNeyazi, T. A., Nadaf, A. H., Tan, K. E., & Schroeder, R. (2024) · Government Information Quarterly · doi:10.1016/j.giq.2024.101980 · Cited by 15
Social bots spoil activist sentiment without eroding engagement
Li, L., Vásárhelyi, O., & Vedres, B. (2024) · Scientific Reports · doi:10.1038/s41598-024-74032-0 · Cited by 16
“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.”
Rodríguez, L. T. (2023) · El Profesional de la Informacion · doi:10.3145/epi.2023.nov.12 · Cited by 23
A Graph Neural Network For Assessing The Affective Coherence Of Twitter Graphs
Drakopoulos, G., Giannoukou, I., Mylonas, P., & Sioutas, S. (2020) · 2020 IEEE International Conference on Big Data (Big Data) · doi:10.1109/bigdata50022.2020.9378492 · Cited by 16
“In the connected era social networks arguably play an instrumental role in reflecting and even shaping up to an extent the public sentiment regarding various social, political, cultural or even historical events [1].”
BackgroundCasero-Ripollés, A., Alonso-Muñoz, L., & Moret-Soler, D. (2025) · Media and Communication · doi:10.17645/mac.9525 · Cited by 15
“Over the past decade, electoral campaigns have been characterized both by the consolidation of new digital platforms and by disinformation (Keller et al., 2020; López et al., 2023).”
Exploring astroturf lobbying in the EU: The case of responsible energy citizen coalition
Lits, B. (2020) · European Policy Analysis · doi:10.1002/epa2.1086 · Cited by 23
Disinformation narratives in Spain: reach, impact and spreading patterns
Suau, J., & Puertas-Graell, D. (2023) · El Profesional de la Informacion · doi:10.3145/epi.2023.sep.08 · Cited by 19
García, S. A., Díaz-Campo, J., & Cambronero-Saiz, B. (2023) · Social Network Analysis and Mining · doi:10.1007/s13278-023-01052-5 · Cited by 29
“…dates, in addition to the high probability of bots, suggests an astroturfing phenomenon or orchestrated support campaign, or both, in some groups using co-tweeting and co-retweeting techniques (Keller et al. 2019) to evade detection by users, platforms and academic studies (Elmas et al. 2021).”
García, S. A., Said-Hung, E. M., & Mottareale, D. (2022) · Revista ICONO14 · doi:10.7195/ri14.v21i1.1890 · Cited by 13
“…o no en este trabajo, es la siguiente: H1: Se está aplicando alrededor del debate político español en Twitter la estrategia Astroturfing para la diseminación de contenido desinformativo, en los términos expuestos por autores como Sorensen et al. (2017), Keller et al. (2019) y Elmas et al. (2021).”
BackgroundInfluentialNavigating the Disinformation Maze: A Bibliometric Analysis of Scholarly Efforts
Tataru, G.-C., Domenteanu, A., Delcea, C., Florescu, M., Orzan, M., & Cotfas, L.-A. (2024) · Inf. · doi:10.3390/info15120742 · Cited by 13
My Brother Helps Me: Node Injection Based Adversarial Attack on Social Bot Detection
Wang, L.-J., Qiao, X., Xie, Y.-W., Nie, W.-Z., Zhang, Y., & Liu, A.-A. (2023) · ACM Multimedia · doi:10.1145/3581783.3612396 · Cited by 13
“Examples of such manipulation include extreme propaganda [1], promotion of political conspiracies [16, 21], and interference in elections [10, 15].”
BackgroundConceptualizing the Evolving Nature of Computational Propaganda: A Systematic Literature Review
Mustafa, H., Luczak-Rösch, M., & Johnstone, D. M. (2025) · Social Science Research Network · doi:10.2139/ssrn.4544686 · Cited by 12
Gross, E.-C., & Balaban, D. C. (2024) · Media and Communication · doi:10.17645/mac.9109 · Cited by 20
“Previous research on disinformation mainly focused on social media platforms such as X, formerly known as Twitter (e.g., Dasilva et al., 2021; Keller et al., 2019; Linvill & Warren, 2020), and Facebook (e.g., Iosifidis & Nicoli, 2020; Jang et al., 2019).”
BackgroundYang, A., & Williams, D. C. (2024) · Social Media + Society · doi:10.1177/20563051241265865 · Cited by 11
“Concerns regarding the impact of disinforma-tion have stimulated a fast-growing body of academic research on this phenomenon (Guo & Vargo, 2020; Keller et al., 2020; Y. M. Kim et al., 2018; Linvill & Warren, 2020; Rojecki & Meraz, 2016).”
InfluentialUnmasking coordinated hate: Analysing hate speech on Spanish digital news media
Arce-García, S., Said-Hung, E., & Montero-Díaz, J. (2024) · New Media & Society · doi:10.1177/14614448241259715 · Cited by 12
“According to Keller et al. (2019), Astroturfing is a ‘common strategy of disinforma-tion, where the disinformation pertains less to the content of the campaign, which can be completely truthful, but to the false impression of independent popular support’.”
InfluentialPropaganda and Manipulation in Mexico: A Programmed, Coordinated and Manipulative “Pink” Campaign
Espinoza, A., & Piña-García, C. A. (2023) · Journalism and Media · doi:10.3390/journalmedia4020037 · Cited by 12
“There is proof that coordinated campaigns through astroturfing are used to improve a brand’s perception or as public relations tool (Kirsch and Chowdhury 2023).”
BackgroundGalgoczy, M. C., Phatak, A., Vinson, D., Mago, V., & Giabbanelli, P. J. (2022) · PeerJ Computer Science · doi:10.7717/peerj-cs.947 · Cited by 20
“Although studies on centrally coordinated disinformation campaigns often focus on how one specific entity (attempts to) shape the public opinion (Keller et al., 2020; Im et al., 2020), complex events involve multiple entities promoting different messages.”
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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