Execution and assessment of agentic influence operations in simulated social networks
On the map: LLM agents and tool use → Social simulation and multi-agent debate
Abstract (arXiv)
This article evaluates AI-enabled influence operations in synthetic social networks through controlled simulations of narrative release, amplification, and counter-messaging. We measure exposure and belief change in agentic audiences, showing that amplification maximizes reach, counter-messaging shifts opinions most, and narrative release requires larger attacker footprints.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 4 of its 15 references that are in the map. First posted on arXiv 27 May 2026.
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- 2024BotSim: LLM-Powered Malicious Social Botnet Simulationcited by 21
- 2025Synthetic generation of online social networks through homophilycited by 4
- 2025Influence Operations in Social Networkscited by 1
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