Unveiling the Truth and Facilitating Change: Towards Agent-based Large-scale Social Movement Simulation

Social media has emerged as a cornerstone of social movements, wielding significant influence in driving societal change. Simulating the response of the public and forecasting the potential impact has become increasingly important. However, existing methods for simulating such phenomena encounter ch...

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Bibliographic Details
Published inarXiv.org
Main Authors Mou, Xinyi, Wei, Zhongyu, Huang, Xuanjing
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 17.06.2024
Subjects
Agent-based models
Digital media
Large language models
Simulation
Social networks
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Summary:Social media has emerged as a cornerstone of social movements, wielding significant influence in driving societal change. Simulating the response of the public and forecasting the potential impact has become increasingly important. However, existing methods for simulating such phenomena encounter challenges concerning their efficacy and efficiency in capturing the behaviors of social movement participants. In this paper, we introduce a hybrid framework HiSim for social media user simulation, wherein users are categorized into two types. Core users are driven by Large Language Models, while numerous ordinary users are modeled by deductive agent-based models. We further construct a Twitter-like environment to replicate their response dynamics following trigger events. Subsequently, we develop a multi-faceted benchmark SoMoSiMu-Bench for evaluation and conduct comprehensive experiments across real-world datasets. Experimental results demonstrate the effectiveness and flexibility of our method.
ISSN:2331-8422