SOTOPIA-S4: a user-friendly system for flexible, customizable, and large-scale social simulation

Xuhui Zhou, Zhe Su, Sophie Feng, Jiaxu Zhou, Jen-tse Huang +7 more
4/19/2025
cs.CYcs.AI

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Abstract

Social simulation through large language model (LLM) agents is a promising approach to explore and validate hypotheses related to social science questions and LLM agents behavior. We present SOTOPIA-S4, a fast, flexible, and scalable social simulation system that addresses the technical barriers of current frameworks while enabling practitioners to generate multi-turn and multi-party LLM-based interactions with customizable evaluation metrics for hypothesis testing. SOTOPIA-S4 comes as a pip package that contains a simulation engine, an API server with flexible RESTful APIs for simulation management, and a web interface that enables both technical and non-technical users to design, run, and analyze simulations without programming. We demonstrate the usefulness of SOTOPIA-S4 with two use cases involving dyadic hiring negotiation and multi-party planning scenarios.

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Cite this paper

@article{zhou2025sotopias,
  title  = {SOTOPIA-S4: a user-friendly system for flexible, customizable, and large-scale social simulation},
  author = {Xuhui Zhou and Zhe Su and Sophie Feng and Jiaxu Zhou and Jen-tse Huang and Hsien-Te Kao and Spencer Lynch and Svitlana Volkova and Tongshuang Sherry Wu and Anita Woolley and Hao Zhu and Maarten Sap},
  year   = {2025},
  eprint = {2504.16122},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2504.16122v1}
}

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