by ValueByte-AI · Agent Tool · ★ 627
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Awesome-LLM-in-Social-Science 🔗 Recommended Resource: Check out Awesome-LLM-Psychometrics for a comprehensive collection of papers and resources on LLM psychometrics, including evaluation, validation, and enhancement. Below we compile awesome papers that evaluate Large Language Models (LLMs) from a perspective of Social Science. align LLMs from a perspective of Social Science. employ LLMs to facilitate research, address issues, and enhance tools in Social Science. contribute surveys, perspectives, and datasets on the above topics. The above taxonomies are by no means orthogonal. For example, evaluations require simulations. We categorize these papers based on our understanding of their focus. This collection has a special focus on Psychology and intrinsic values. Welcome to contribute and discuss! 🤩 Papers marked with a ⭐️ are contributed by the maintainers of this repository. If you find them useful, we would greatly appreciate it if you could give the repository a star and cite our paper.
| Stars | 627 |
| Forks | 49 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 32.75/100 |
| Last Updated | 2026-06-08 |
| Created | 2023-10-15 |
| Est. Tokens | ~13k |
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Awesome-LLM-in-Social-Science is Awesome papers involving LLMs in Social Science.. It is categorized as a Agent Tool with 627 GitHub stars.
You can find installation instructions and usage details in the Awesome-LLM-in-Social-Science GitHub repository at github.com/ValueByte-AI/Awesome-LLM-in-Social-Science. The project has 627 stars and 49 forks, indicating an active community.
Awesome-LLM-in-Social-Science is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Awesome-LLM-in-Social-Science on Agent Skills Hub include Auto-Empirical-Research-Skills, LLMCompiler, Awesome-Agent-Skills-for-Empirical-Research. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.