title: SocioVerse: A World Model for Social Simulation Powered by LLM Agents
    and A Pool of 10 Million Real-World Users
summary: Social simulation is transforming traditional social science research by
  modeling human behavior through interactions between virtual individuals and
  their environments. With recent advances in large language models (LLMs), this
  approach has shown growing potential in capturing individual differences and
  predicting group behaviors. However, existing methods face alignment challenges
  related to the environment, target users, interaction mechanisms, and
  behavioral patterns. To this end, we introduce SocioVerse, an LLM-agent-driven
  world model for social simulation. Our framework features four powerful
  alignment components and a user pool of 10 million real individuals. To
  validate its effectiveness, we conducted large-scale simulation experiments
  across three distinct domains: politics, news, and economics. Results
  demonstrate that SocioVerse can reflect large-scale population dynamics while
  ensuring diversity, credibility, and representativeness through standardized
  procedures and minimal manual adjustments.
paper_authors._id: 67fdc9adc47ae882c7a17c8a
paper_authors.name: Xinnong Zhang
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paper_authors.fullname: xnzhang
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paper_authors.user: Lishi0905
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paper_authors.name: Jiayu Lin
paper_authors._id: 67fdc9adc47ae882c7a17c8c
paper_authors.name: Xinyi Mou
paper_authors._id: 67fdc9adc47ae882c7a17c8d
paper_authors.name: Shiyue Yang
paper_authors._id: 67fdc9adc47ae882c7a17c8e
paper_authors.name: Xiawei Liu
paper_authors._id: 67fdc9adc47ae882c7a17c8f
paper_authors.name: Libo Sun
paper_authors.status: admin_assigned
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paper_authors.fullname: Libo Sun
paper_authors.type: user
paper_authors.user: libo-ca
paper_authors._id: 67fdc9adc47ae882c7a17c90
paper_authors.name: Hanjia Lyu
paper_authors._id: 67fdc9adc47ae882c7a17c91
paper_authors.name: Yihang Yang
paper_authors._id: 67fdc9adc47ae882c7a17c92
paper_authors.name: Weihong Qi
paper_authors._id: 67fdc9adc47ae882c7a17c93
paper_authors.name: Yue Chen
paper_authors._id: 67fdc9adc47ae882c7a17c94
paper_authors.name: Guanying Li
paper_authors._id: 67fdc9adc47ae882c7a17c95
paper_authors.name: Ling Yan
paper_authors._id: 67fdc9adc47ae882c7a17c96
paper_authors.name: Yao Hu
paper_authors._id: 67fdc9adc47ae882c7a17c97
paper_authors.name: Siming Chen
paper_authors.status: admin_assigned
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paper_authors.avatarUrl: /avatars/5e74fbdff4d9145c2d0b3c2c4c0145c7.svg
paper_authors.fullname: Siming
paper_authors.type: user
paper_authors.user: SimingChen
paper_authors._id: 67fdc9adc47ae882c7a17c98
paper_authors.name: Yu Wang
paper_authors._id: 67fdc9adc47ae882c7a17c99
paper_authors.name: Jingxuan Huang
paper_authors._id: 67fdc9adc47ae882c7a17c9a
paper_authors.name: Jiebo Luo
paper_authors._id: 67fdc9adc47ae882c7a17c9b
paper_authors.name: Shiping Tang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-04-15T08:28:00.350Z
paper_authors._id: 64b7727a88b86014d7eb9073
paper_authors.avatarUrl: /avatars/bc4dda32363efcc16212b8eb97c2f813.svg
paper_authors.fullname: Simon Tang
paper_authors.type: user
paper_authors.user: tangshiping
paper_authors._id: 67fdc9adc47ae882c7a17c9c
paper_authors.name: Libo Wu
paper_authors._id: 67fdc9adc47ae882c7a17c9d
paper_authors.name: Baohua Zhou
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-04-15T08:27:40.001Z
paper_authors._id: 67d066e70fdab2f434aa1488
paper_authors.avatarUrl: /avatars/d17838856185856306ec5d4a121314f1.svg
paper_authors.fullname: Baohua Zhou
paper_authors.type: user
paper_authors.user: milesz7777
paper_authors._id: 67fdc9adc47ae882c7a17c9e
paper_authors.name: Zhongyu Wei
paper_title: SocioVerse: A World Model for Social Simulation Powered by LLM Agents
    and A Pool of 10 Million Real-World Users
paper_summary: Social simulation is transforming traditional social science research by
  modeling human behavior through interactions between virtual individuals and
  their environments. With recent advances in large language models (LLMs), this
  approach has shown growing potential in capturing individual differences and
  predicting group behaviors. However, existing methods face alignment challenges
  related to the environment, target users, interaction mechanisms, and
  behavioral patterns. To this end, we introduce SocioVerse, an LLM-agent-driven
  world model for social simulation. Our framework features four powerful
  alignment components and a user pool of 10 million real individuals. To
  validate its effectiveness, we conducted large-scale simulation experiments
  across three distinct domains: politics, news, and economics. Results
  demonstrate that SocioVerse can reflect large-scale population dynamics while
  ensuring diversity, credibility, and representativeness through standardized
  procedures and minimal manual adjustments.
paper_ai_summary: SocioVerse, an LLM-agent-driven world model, effectively simulates social behaviors and dynamics across various domains with standardized procedures and minimal manual adjustments.
paper_ai_keywords: large language models LLM-agent-driven world model alignment components population dynamics diversity credibility representativeness