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 polarizat ion, 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. Recent advancements in machine learning, particularly in Large Language Models (LLMs), have substantially enhanced the capability of machines to emulate human language patterns, cognitive processes, and interactive behaviors [1].