Simulating Influence Dynamics with LLM Agents
Fuente:
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_ | 1866915192263147520 |
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| author | Nasim, Mehwish Gilani, Syed Muslim Qasmi, Amin Naseem, Usman |
| author_facet | Nasim, Mehwish Gilani, Syed Muslim Qasmi, Amin Naseem, Usman |
| contents | This paper introduces a simulator designed for opinion dynamics researchers to model competing influences within social networks in the presence of LLM-based agents. By integrating established opinion dynamics principles with state-of-the-art LLMs, this tool enables the study of influence propagation and counter-misinformation strategies. The simulator is particularly valuable for researchers in social science, psychology, and operations research, allowing them to analyse societal phenomena without requiring extensive coding expertise. Additionally, the simulator will be openly available on GitHub, ensuring accessibility and adaptability for those who wish to extend its capabilities for their own research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_08709 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Simulating Influence Dynamics with LLM Agents Nasim, Mehwish Gilani, Syed Muslim Qasmi, Amin Naseem, Usman Social and Information Networks Artificial Intelligence I.2.7; I.6.0 This paper introduces a simulator designed for opinion dynamics researchers to model competing influences within social networks in the presence of LLM-based agents. By integrating established opinion dynamics principles with state-of-the-art LLMs, this tool enables the study of influence propagation and counter-misinformation strategies. The simulator is particularly valuable for researchers in social science, psychology, and operations research, allowing them to analyse societal phenomena without requiring extensive coding expertise. Additionally, the simulator will be openly available on GitHub, ensuring accessibility and adaptability for those who wish to extend its capabilities for their own research. |
| title | Simulating Influence Dynamics with LLM Agents |
| topic | Social and Information Networks Artificial Intelligence I.2.7; I.6.0 |
| url | https://arxiv.org/abs/2503.08709 |