Towards Simulating Social Influence Dynamics with LLM-based Multi-agents
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866909712209936384 |
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| author | Lin, Hsien-Tsung Huang, Pei-Cing Ku, Chan-Tung Hsu, Chan Shieh, Pei-Xuan Kang, Yihuang |
| author_facet | Lin, Hsien-Tsung Huang, Pei-Cing Ku, Chan-Tung Hsu, Chan Shieh, Pei-Xuan Kang, Yihuang |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_22467 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Simulating Social Influence Dynamics with LLM-based Multi-agents Lin, Hsien-Tsung Huang, Pei-Cing Ku, Chan-Tung Hsu, Chan Shieh, Pei-Xuan Kang, Yihuang Multiagent Systems Artificial Intelligence Computers and Society 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. |
| title | Towards Simulating Social Influence Dynamics with LLM-based Multi-agents |
| topic | Multiagent Systems Artificial Intelligence Computers and Society |
| url | https://arxiv.org/abs/2507.22467 |