Siying Wang ¹ , Xuan Wang ² , Yining Tang ³ and Chao Wu ³ , ¹ Renmin University of China, China, ² China Media Group, China, ³ Zhejiang University, China

Simulating public opinion evolution is a core focus of computational social science. Traditional agent-based models rely on predefined heuristic rules, failing to capture the semantic features and cognitive processes of human natural language interactions. While large language models offer new approaches for artificial society construction, existing frameworks have limitations in scalability and memory management. Taking the Fukushima nuclear wastewater discharge event as the background, this study uses an open-source multi-agent social simulation framework, designing four progressive intervention scenarios to analyze agents' cognitive synergy and public opinion trajectories. Results show the framework mitigates role drift and premature consensus, reproduces the public opinion evolution trajectory, providing empirical insights for policy testing and LLM-driven social computing.

Multi-agent simulation, Public opinion evolution, Nuclear wastewater discharge, Computational social science