{"data":{"slug":"valuebyte-ai-awesome-llm-in-social-science","name":"Awesome-LLM-in-Social-Science","tagline":"Awesome papers involving LLMs in Social Science","github_url":"https://github.com/ValueByte-AI/Awesome-LLM-in-Social-Science","owner":"ValueByte-AI","repo":"Awesome-LLM-in-Social-Science","owner_avatar_url":"https://avatars.githubusercontent.com/u/151605979?v=4","primary_language":null,"stars":639,"forks":48,"topics":["alignment","economics","large-language-models","llm-agent","llm-evaluation","llms","policy","psychology","simulation-environment","social-network","social-science"],"archived":false,"github_pushed_at":"2026-06-08T12:11:59+00:00","maintenance_label":"Steady","url":"https://www.graphcanon.com/tools/valuebyte-ai-awesome-llm-in-social-science","markdown_url":"https://www.graphcanon.com/tools/valuebyte-ai-awesome-llm-in-social-science.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/valuebyte-ai-awesome-llm-in-social-science","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=valuebyte-ai-awesome-llm-in-social-science","description":"Awesome papers involving LLMs in Social Science.","homepage_url":null,"license":"MIT","open_issues":0,"watchers":15,"ai_summary":"A collection of research papers focusing on the application and implications of large language models (LLMs) within the domain of social science. The repository explores various topics, including alignment, economics, policy, psychology, and more.","readme_excerpt":"# Awesome-LLM-in-Social-Science\n\n\n\n> **🔗 Recommended Resource:**  \n> Check out [Awesome-LLM-Psychometrics](https://github.com/ValueByte-AI/Awesome-LLM-Psychometrics) for a comprehensive collection of papers and resources on LLM psychometrics, including evaluation, validation, and enhancement.  \n>  \n\n\n\n\nBelow we compile *awesome* papers that  \n- **evaluate** Large Language Models (LLMs) from a perspective of Social Science.\n- **align** LLMs from a perspective of Social Science.\n- employ LLMs to **facilitate research, address issues, and enhance tools** in Social Science.\n- contribute **surveys**, **perspectives**, and **datasets** on the above topics.\n\nThe 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**.\n\nWelcome to contribute and discuss!\n\n---\n\n🤩 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.\n\n\n```bibtex\n@article{ye2025large,\n  title={Large Language Model Psychometrics: A Systematic Review of Evaluation, Validation, and Enhancement},\n  author={Ye, Haoran and Jin, Jing and Xie, Yuhang and Zhang, Xin and Song, Guojie},\n  journal={arXiv preprint arXiv:2505.08245},\n  year={2025},\n  note={Project website: \\url{https://llm-psychometrics.com}, GitHub: \\url{https://github.com/ValueByte-AI/Awesome-LLM-Psychometrics}}\n}\n```\n\n\n---\n\n## Table of Contents\n\n* 1. [📚 Survey](#Survey)\n* 2. [🗂️ Dataset](#Dataset)\n* 3. [🔎 Evaluating LLM](#EvaluatingLLM)\n\t* 3.1. [❤️ Value](#Value)\n\t* 3.2. [🩷 Personality](#Personality)\n\t* 3.3. [🔞 Morality](#Morality)\n\t* 3.4. [🎤 Opinion](#Opinion)\n\t* 3.5. [💚 General Preference](#GeneralPreference)\n\t* 3.6. [🧠 Ability](#Ability)\n\t* 3.7. [⚠️ Risk](#Risk) \n* 4. [⚒️ Tool enhancement](#Toolenhancement)\n* 5. [⛑️ Alignment](#Alignment)\n\t* 5.1. [🌈 Pluralistic Alignment](#PluralisticAlignment)\n* 6. [🚀 Simulation](#Simulation)\n* 7. [👁️‍🗨️ Perspective and Position](#Perspective)\n\n\n---\n\n##  1. <a name='Survey'></a>📚 Survey \n- ⭐️ **Large Language Model Psychometrics: A Systematic Review of Evaluation, Validation, and Enhancement**, 2025.05, [[paper]](https://arxiv.org/abs/2505.08245).\n- **Missing the Margins: A Systematic Literature Review on the Demographic Representativeness of LLMs**, ACL 2025, [[paper]](https://aclanthology.org/2025.findings-acl.1246/), [[collection]](https://github.com/Indiiigo/LLM_rep_review).\n- **Large language models (LLM) in computational social science: prospects, current state, and challenges**, 2025.03, Social Network Analysis and Mining, [[paper]](https://link.springer.com/article/10.1007/s13278-025-01428-9).\n- **Towards Scientific Intelligence: A Survey of LLM-based Scientific Agents**, 2025.03, [[paper]](https://arxiv.org/abs/2503.24047).\n- **On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective**, 2025.02, [[paper]](https://arxiv.org/abs/2502.14296).\n- **The Road to Artificial SuperIntelligence: A Comprehensive Survey of Superalignment**, 2024.12, [[paper]](https://arxiv.org/abs/2412.16468).\n- **Large Language Model Safety: A Holistic Survey**, 2024.12, [[paper]](https://arxiv.org/abs/2412.17686).\n- **Political-LLM: Large Language Models in Political Science**, 2024.12, [[paper]](https://arxiv.org/abs/2412.06864), [[website]](https://political-llm.org/).\n- **LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods**, 2024.12, [[paper]](https://arxiv.org/abs/2412.05579).\n- **From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents**, 2024.12, [[paper]](https://arxiv.org/abs/2412.03563), [[repo]](https://github.com/FudanDISC/SocialAgent).\n- **A Survey on Human-Centric LLMs**, 2024.11, [[paper]](https://arxiv.org/abs/2411.14491).\n- **Survey of Cultural Aware","github_created_at":"2023-10-15T13:34:33+00:00","created_at":"2026-07-11T11:59:54.000754+00:00","updated_at":"2026-07-28T12:00:54.545266+00:00","categories":[{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"alignment","name":"alignment"},{"slug":"economics","name":"economics"},{"slug":"large-language-models","name":"large language models"},{"slug":"llm-agent","name":"llm-agent"},{"slug":"llm-evaluation","name":"llm-evaluation"},{"slug":"policy","name":"policy"},{"slug":"psychology","name":"psychology"},{"slug":"simulation-environment","name":"simulation-environment"}],"trust":{"provenance":{"is_fork":false,"github_id":705247308,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-28T12:00:53.813Z","maintenance":{"label":"Steady","score":60,"methodology":"github_public_v1","releases_90d":0,"days_since_push":49,"last_release_at":null},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:59:55.320Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-28T12:00:54.269Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-07-28T12:00:54.269Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["Need to explore academic insights into LLM impacts on specific social areas","Interested in detailed case studies on ethics and social policies regarding AI"],"when_not_to_use":["Looking for a hands-on coding or practical implementation guide of LLMs","In need of real-time data analysis tools for immediate social science research outcomes"],"source":"enrich:decision_facts","observed_at":"2026-07-12T10:48:27.717Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Curate research papers on LLM applications in social science, covering topics like alignment, economics, policy, psychology, and more."}]}}