Understanding Dynamic Diffusion Process of LLM-based Agents under Information Asymmetry

ACL ARR 2025 February Submission3873 Authors

Abstract: Large language models have been used to simulate human society using multi-agent systems. Most current social simulation research emphasizes interactive behaviors in fixed environments, ignoring information opacity, relationship variability and diffusion diversity. In this paper, we study the dynamics of information diffusion in 12 asymmetric open environments defined by information content and distribution mechanisms. We first present a general framework to capture the features of information diffusion. Then, we designed a dynamic attention mechanism to help agents allocate attention to different information, addressing the limitations of LLM-based attention. Agents start by responding to external information stimuli within a five-agent group, increasing group size and forming information circles while developing relationships and sharing information. Additionally, we observe the emergence of information cocoons, the evolution of information gaps, and the accumulation of social capital, which are closely linked to psychological, sociological, and communication theories.

Paper Type: Long

Research Area: Computational Social Science and Cultural Analytics

Research Area Keywords: large language model, multi-agent system, social simulation, information asymmetry

Languages Studied: English

Submission Number: 3873