This research introduces a synthetic simulation framework for evaluating online moderation strategies without human participants, enabling large-scale testing of different approaches.

• Uses LLMs to simulate human discussants, moderators, and evaluators
• Allows systematic comparison of different moderation policies and strategies
• Creates reproducible experiments that would be impractical with human participants
• Provides a cost-effective way to improve content moderation systems

Why it matters for security: This approach helps platforms develop more effective content moderation systems to protect users from harmful content, enabling rapid testing of moderation policies before deployment in real-world environments where security risks exist.

Read the full paper: Scalable Evaluation of Online Moderation Strategies via Synthetic Simulations