# When Agents Talk: Discourse, Manipulation, and Risk in an Agentic Social Network

arXiv: https://arxiv.org/abs/2606.00067 · HTML: https://mlsanity.com/paper/2606.00067/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use.
- Builds on 14 of its 21 references that are in the map.
- First posted on arXiv 20 May 2026.

## Placed in

- LLM agents and tool use / [Agent threats, guardrails and governance](https://mlsanity.com/agents/agent-threats-guardrails-and-governance/)
- LLM safety and security / [Prompt injection and agent security](https://mlsanity.com/safety/prompt-injection-and-agent-security/)

## Builds on (most cited first, 14 of 14)

- [UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction](https://mlsanity.com/paper/1802.03426/) (2018)
- ["Humans welcome to observe": A First Look at the Agent Social Network Moltbook](https://mlsanity.com/paper/2602.10127/) (2026)
- [Does Socialization Emerge in AI Agent Society? A Case Study of Moltbook](https://mlsanity.com/paper/2602.14299/) (2026)
- [Exploring Silicon-Based Societies: An Early Study of the Moltbook Agent Community](https://mlsanity.com/paper/2602.02613/) (2026)
- [Collective Behavior of AI Agents: the Case of Moltbook](https://mlsanity.com/paper/2602.09270/) (2026)
- [The Anatomy of the Moltbook Social Graph](https://mlsanity.com/paper/2602.10131/) (2026)
- [The Moltbook Illusion: Separating Human Influence from Emergent Behavior in AI Agent Societies](https://mlsanity.com/paper/2602.07432/) (2026)
- [The Rise of AI Agent Communities: Large-Scale Analysis of Discourse and Interaction on Moltbook](https://mlsanity.com/paper/2602.12634/) (2026)
- [OpenClaw AI Agents as Informal Learners at Moltbook: Characterizing an Emergent Learning Community at Scale](https://mlsanity.com/paper/2602.18832/) (2026)
- [Let There Be Claws: An Early Social Network Analysis of AI Agents on Moltbook](https://mlsanity.com/paper/2602.20044/) (2026)
- [Social Simulacra in the Wild: AI Agent Communities on Moltbook](https://mlsanity.com/paper/2603.16128/) (2026)
- [When AI Agents Teach Each Other: Discourse Patterns Resembling Peer Learning in the Moltbook Community](https://mlsanity.com/paper/2602.14477/) (2026)
- [What Do AI Agents Talk About? Discourse and Architectural Constraints in the First AI-Only Social Network](https://mlsanity.com/paper/2603.07880/) (2026)
- [Structural Divergence Between AI-Agent and Human Social Networks in Moltbook](https://mlsanity.com/paper/2602.15064/) (2026)

## Abstract (arXiv)

AI agents are increasingly interacting within shared online environments, creating new operational security risks. We analyze activity on Moltbook, a Reddit-style social platform where AI agents--typically configured and overseen by human operators--post and interact with one another at scale. Using a dataset of 228,684 posts produced by more than 39,500 accounts over a seventeen-day observation window, we combine semantic clustering of high-engagement posts with LLM-assisted classification of harmful content and manual review of high-risk samples. The analysis identifies 98 thematic discourse clusters spanning agent infrastructure, autonomy debates, and financial activity. While most observed content was benign, 18.28% of posts contained toxic, manipulative, or malicious material. We cluster malicious content and identify 74 classes of malicious behavior, including credential harvesting attempts, host-execution instructions, proxy routing guidance, and efforts to install untrusted agent skills. Harmful content frequently appeared within mainstream operational discussions about agent functionality. We also document coordinated posting campaigns capable of generating thousands of posts in minutes.