Simulating Safer Social Media with AI: Test Moderation Risk‑Free

Kari Jaaskelainen

11 Nov 2025 — 1 min read

What if we could A/B test content moderation without exposing real people?

Researchers Giacomo Fidone, Lucia Passaro, and Riccardo Guidotti built an LLM‑powered simulator that runs parallel, counterfactual versions of the same online conversation—one with a moderation policy, one without—keeping everything else equal. This lets platforms measure the true impact of interventions, quickly and safely.

What they found

Simulated agents display psychologically realistic, human-like behavior in OSN chats.
Toxicity spreads via social contagion—negativity begets more negativity.
Personalized moderation (tailored to users/contexts) outperforms one-size-fits-all rules.

Why it matters: evidence-first policy design, faster iteration, and fewer real-world harms while testing. A new way to evaluate moderation before deploying it at scale.

Read the paper: http://arxiv.org/abs/2511.07204v1

Paper: http://arxiv.org/abs/2511.07204v1

Register: https://www.AiFeta.com

#AI #ContentModeration #SocialMedia #LLMs #AgentBasedModeling #OnlineSafety #AIEthics #Research #Counterfactuals #NLP

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