Zichen Cheng , Ziyue Lin , Yihang Yang , Zhongyu Wei , Siming Chen
{"title":"基于法学硕士的多智能体建模的社交媒体事件动态交互仿真和可视化分析","authors":"Zichen Cheng , Ziyue Lin , Yihang Yang , Zhongyu Wei , Siming Chen","doi":"10.1016/j.visinf.2025.100260","DOIUrl":null,"url":null,"abstract":"<div><div>With the increasing role of social media in information dissemination, effectively simulating and analyzing public event dynamics has become a key research focus. We present an interactive visual analysis system for simulating social media events using multi-agent models powered by large language models (LLMs). By modeling agents with diverse characteristics, the system explores how agents perceive information, adjust their emotions and stances, provide feedback, and influence the trajectory of events. The system integrates real-time interactive simulation with multi-perspective visualization, enabling users to investigate event trajectories and key influencing factors under varied configurations. Theoretical work standardizes agent attributes and interaction mechanisms, supporting realistic simulation of social media behaviors. Evaluation through indicators and case studies demonstrates the system’s effectiveness and adaptability, offering a novel tool for public event analysis across open social platforms.</div></div>","PeriodicalId":36903,"journal":{"name":"Visual Informatics","volume":"9 3","pages":"Article 100260"},"PeriodicalIF":3.8000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Interactive simulation and visual analysis of social media event dynamics with LLM-based multi-agent modeling\",\"authors\":\"Zichen Cheng , Ziyue Lin , Yihang Yang , Zhongyu Wei , Siming Chen\",\"doi\":\"10.1016/j.visinf.2025.100260\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>With the increasing role of social media in information dissemination, effectively simulating and analyzing public event dynamics has become a key research focus. We present an interactive visual analysis system for simulating social media events using multi-agent models powered by large language models (LLMs). By modeling agents with diverse characteristics, the system explores how agents perceive information, adjust their emotions and stances, provide feedback, and influence the trajectory of events. The system integrates real-time interactive simulation with multi-perspective visualization, enabling users to investigate event trajectories and key influencing factors under varied configurations. Theoretical work standardizes agent attributes and interaction mechanisms, supporting realistic simulation of social media behaviors. Evaluation through indicators and case studies demonstrates the system’s effectiveness and adaptability, offering a novel tool for public event analysis across open social platforms.</div></div>\",\"PeriodicalId\":36903,\"journal\":{\"name\":\"Visual Informatics\",\"volume\":\"9 3\",\"pages\":\"Article 100260\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Visual Informatics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468502X25000439\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Visual Informatics","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468502X25000439","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Interactive simulation and visual analysis of social media event dynamics with LLM-based multi-agent modeling
With the increasing role of social media in information dissemination, effectively simulating and analyzing public event dynamics has become a key research focus. We present an interactive visual analysis system for simulating social media events using multi-agent models powered by large language models (LLMs). By modeling agents with diverse characteristics, the system explores how agents perceive information, adjust their emotions and stances, provide feedback, and influence the trajectory of events. The system integrates real-time interactive simulation with multi-perspective visualization, enabling users to investigate event trajectories and key influencing factors under varied configurations. Theoretical work standardizes agent attributes and interaction mechanisms, supporting realistic simulation of social media behaviors. Evaluation through indicators and case studies demonstrates the system’s effectiveness and adaptability, offering a novel tool for public event analysis across open social platforms.