{"work":{"id":"ae6d9bb2-30d7-4b8c-8140-bcb69cc5c24c","openalex_id":"https://openalex.org/W2552170990","doi":"10.1146/annurev-soc-060116-053450","arxiv_id":"2307.14984","raw_key":null,"title":"S$^3$: Social-network Simulation System with Large Language Model-Empowered Agents","authors":null,"authors_text":"Chen Gao, Xiaochong Lan, Zhihong Lu, Jinzhu Mao, Jinghua Piao, Huandong Wang","year":2023,"venue":"cs.SI","abstract":"Social network simulation plays a crucial role in addressing various challenges within social science. It offers extensive applications such as state prediction, phenomena explanation, and policy-making support, among others. In this work, we harness the formidable human-like capabilities exhibited by large language models (LLMs) in sensing, reasoning, and behaving, and utilize these qualities to construct the S$^3$ system (short for $\\textbf{S}$ocial network $\\textbf{S}$imulation $\\textbf{S}$ystem). Adhering to the widely employed agent-based simulation paradigm, we employ prompt engineering and prompt tuning techniques to ensure that the agent's behavior closely emulates that of a genuine human within the social network. Specifically, we simulate three pivotal aspects: emotion, attitude, and interaction behaviors. By endowing the agent in the system with the ability to perceive the informational environment and emulate human actions, we observe the emergence of population-level phenomena, including the propagation of information, attitudes, and emotions. We conduct an evaluation encompassing two levels of simulation, employing real-world social network data. Encouragingly, the results demonstrate promising accuracy. This work represents an initial step in the realm of social network simulation empowered by LLM-based agents. We anticipate that our endeavors will serve as a source of inspiration for the development of simulation systems within, but not limited to, social science.","external_url":"https://arxiv.org/abs/2307.14984","cited_by_count":316,"metadata_source":"pith","metadata_fetched_at":"2026-08-05T02:28:24.338817+00:00","pith_arxiv_id":"2307.14984","created_at":"2026-05-10T06:41:36.812801+00:00","updated_at":"2026-08-05T02:28:24.338817+00:00","title_quality_ok":true,"display_title":"S$^3$: Social-network Simulation System with Large Language Model-Empowered Agents","render_title":"S$^3$: Social-network Simulation System with Large Language Model-Empowered Agents"},"hub":{"state":{"work_id":"ae6d9bb2-30d7-4b8c-8140-bcb69cc5c24c","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":39,"external_cited_by_count":316,"distinct_field_count":7,"first_pith_cited_at":"2023-08-22T13:30:37+00:00","last_pith_cited_at":"2026-07-07T11:34:10+00:00","author_build_status":"not_needed","summary_status":"needed","contexts_status":"needed","graph_status":"needed","ask_index_status":"not_needed","reader_status":"not_needed","recognition_status":"not_needed","updated_at":"2026-08-22T04:19:30.443665+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"background","n":9}],"polarity_counts":[{"context_polarity":"background","n":9}],"runs":{},"summary":{},"graph":{},"authors":[]}}