Related papers: MASim: Multilingual Agent-Based Simulation for Social Science

MASim: Multilingual Agent-Based Simulation for Social Science

URL: http://arxiv.org/abs/2512.07195v1
Date: Mon, 08 Dec 2025 06:12:48 GMT
Title: MASim: Multilingual Agent-Based Simulation for Social Science
Authors: Xuan Zhang, Wenxuan Zhang, Anxu Wang, See-Kiong Ng, Yang Deng,
Abstract summary: Multi-agent role-playing has recently shown promise for studying social behavior with language agents.<n>Existing simulations are mostly monolingual and fail to model cross-lingual interaction.<n>We introduce MASim, the first multilingual agent-based simulation framework.
Score: 68.04129327237963
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Multi-agent role-playing has recently shown promise for studying social behavior with language agents, but existing simulations are mostly monolingual and fail to model cross-lingual interaction, an essential property of real societies. We introduce MASim, the first multilingual agent-based simulation framework that supports multi-turn interaction among generative agents with diverse sociolinguistic profiles. MASim offers two key analyses: (i) global public opinion modeling, by simulating how attitudes toward open-domain hypotheses evolve across languages and cultures, and (ii) media influence and information diffusion, via autonomous news agents that dynamically generate content and shape user behavior. To instantiate simulations, we construct the MAPS benchmark, which combines survey questions and demographic personas drawn from global population distributions. Experiments on calibration, sensitivity, consistency, and cultural case studies show that MASim reproduces sociocultural phenomena and highlights the importance of multilingual simulation for scalable, controlled computational social science.

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