Exposing influence campaigns in the age of LLMs: a behavioral-based AI approach to detecting state-sponsored trolls
Fatima Ezzeddine, Omran Ayoub, Silvia Giordano, Gianluca Nogara, Ihab Sbeity, Emilio Ferrara, Luca Luceri
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Exposing influence campaigns in the age of LLMs: a behavioral-based AI approach to detecting state-sponsored trolls presents a leverage (statistics) approach for classifier (uml).
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Evidence disclosure
Evidence graph: 2 refs, 1 links.
Utility signals: depth 65/100, grounding 58/100, status medium.
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Research context
17
Citations
50
References
Tasks
Classifier (UML), Realm, Social media, Computer science, Context (archaeology), Replicate, Psychology, Social psychology
Methods
Leverage (statistics), Language model
Domains
Artificial intelligence, Machine learning, Computer security
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