by yunshiuan · Agent Tool · ★ 43
Simulating Opinion Dynamics with Networks of LLM-based Agents Yun-Shiuan Chuang, Agam Goyal, Nikunj Harlalka, Siddharth Suresh, Robert Hawkins, Sijia Yang, Dhavan Shah, Junjie Hu, Timothy T. Rogers University of Wisconsin - Madison Accurately simulating human opinion dynamics is crucial for understanding a variety of societal phenomena, including polarization and the spread of misinformation. However, the agent based models (ABMs) commonly used for such simulations often over-simplify human behavior.
| Stars | 43 |
| Forks | 4 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 60.8596800308234/100 |
| Open Issues | 3 |
| Last Updated | 2024-06-26 |
| Created | 2024-03-31 |
| Platforms | python |
| Est. Tokens | ~58k |
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llm-agent-opinion-dynamics is The repository for the scripts and materials for the paper "Simulating Opinion Dynamics with Networks of LLM-based Agents".". It is categorized as a Agent Tool with 43 GitHub stars.
llm-agent-opinion-dynamics is primarily written in Python.
You can find installation instructions and usage details in the llm-agent-opinion-dynamics GitHub repository at github.com/yunshiuan/llm-agent-opinion-dynamics. The project has 43 stars and 4 forks, indicating an active community.
llm-agent-opinion-dynamics is released under the MIT license, making it free to use and modify according to the license terms.