Towards Simulating Social Influence Dynamics with LLM-based Multi-agents

Recent advancements in Large Language Models offer promising capabilities to simulate complex human social interactions. We investigate whether LLM-based multi-agent simulations can reproduce core human social dynamics observed in online forums. We evaluate conformity dynamics, group polarization, and fragmentation across different model scales and reasoning capabilities using a structured simulation framework. Our findings indicate that smaller models exhibit higher conformity rates, whereas models optimized for reasoning are more resistant to social influence.

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ArXiv.org
Published
2025-07-30
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Topic Modeling
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article

Towards Simulating Social Influence Dynamics with LLM-based Multi-agents

ArXiv.org
Topic Modeling
article

Towards Simulating Social Influence Dynamics with LLM-based Multi-agents

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Abstract

Recent advancements in Large Language Models offer promising capabilities to simulate complex human social interactions. We investigate whether LLM-based multi-agent simulations can reproduce core human social dynamics observed in online forums. We evaluate conformity dynamics, group polarization, and fragmentation across different model scales and reasoning capabilities using a structured simulation framework. Our findings indicate that smaller models exhibit higher conformity rates, whereas models optimized for reasoning are more resistant to social influence.

ArXiv.org
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Topic Modeling
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Towards Simulating Social Influence Dynamics with LLM-based Multi-agents · ArXiv.org (2025) | TGRS Research Map | TGRS