Coordinated Reply Attacks in Influence Operations: Characterization and Detection

Coordinated reply attacks are a tactic observed in online influence operations and other coordinated campaigns to support or harass targeted individuals, or influence them or their followers. Despite its potential to influence the public, past studies have yet to analyze or provide a methodology to detect this tactic. In this study, we characterize coordinated reply attacks in the context of influence operations on Twitter. Our analysis reveals that the primary targets of these attacks are influential people such as journalists, news media, state officials, and politicians. We propose two supervised machine-learning models, one to classify tweets to determine whether they are targeted by a reply attack, and one to classify accounts that reply to a targeted tweet to determine whether they are part of a coordinated attack. The classifiers achieve AUC scores of 0.88 and 0.97, respectively. These results indicate that accounts involved in reply attacks can be detected, and the targeted accounts themselves can serve as sensors for influence operation detection.

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Institutions

Publication Details

Journal
Proceedings of the International AAAI Conference on Web and Social Media
Published
2025-06-07
DOI
https://doi.org/10.1609/icwsm.v19i1.35889
Citations
2
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
2.97

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article

Coordinated Reply Attacks in Influence Operations: Characterization and Detection

Alessandro Flammini, Manita Pote, Filippo Menczer, Tuğrulcan Elmas
2 citations
Proceedings of the International AAAI Conference on Web and Social Media
Network Security and Intrusion Detection
2.97
article

Coordinated Reply Attacks in Influence Operations: Characterization and Detection

Alessandro Flammini, Manita Pote, Filippo Menczer, Tuğrulcan Elmas
article en
2 citations

Abstract

Coordinated reply attacks are a tactic observed in online influence operations and other coordinated campaigns to support or harass targeted individuals, or influence them or their followers. Despite its potential to influence the public, past studies have yet to analyze or provide a methodology to detect this tactic. In this study, we characterize coordinated reply attacks in the context of influence operations on Twitter. Our analysis reveals that the primary targets of these attacks are influential people such as journalists, news media, state officials, and politicians. We propose two supervised machine-learning models, one to classify tweets to determine whether they are targeted by a reply attack, and one to classify accounts that reply to a targeted tweet to determine whether they are part of a coordinated attack. The classifiers achieve AUC scores of 0.88 and 0.97, respectively. These results indicate that accounts involved in reply attacks can be detected, and the targeted accounts themselves can serve as sensors for influence operation detection.

Proceedings of the International AAAI Conference on Web and Social MediaVol. 19
Indiana University Bloomington (US), University of Edinburgh (GB)
Eli Lilly and Company, John S. and James L. Knight Foundation, Lilly Endowment, Craig Newmark Philanthropies, Defense Advanced Research Projects Agency
Openalex Percentile: Top 8%
Network Security and Intrusion Detection
2.97
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