[2602.03775] An Empirical Study of Collective Behaviors and Social Dynamics in Large Language Model Agents

Computer Science > Social and Information Networks arXiv:2602.03775 (cs) [Submitted on 3 Feb 2026 (v1), last revised 27 Feb 2026 (this version, v2)] Title:An Empirical Study of Collective Behaviors and Social Dynamics in Large Language Model Agents Authors:Farnoosh Hashemi, Michael W. Macy View a PDF of the paper titled An Empirical Study of Collective Behaviors and Social Dynamics in Large Language Model Agents, by Farnoosh Hashemi and Michael W. Macy View PDF HTML (experimental) Abstract:Large Language Models (LLMs) increasingly mediate our social, cultural, and political interactions. While they can simulate some aspects of human behavior and decision-making, it is still underexplored whether repeated interactions with other agents amplify their biases or lead to exclusionary behaviors. To this end, we study this http URL-an LLM-driven social media platform-analyzing 7M posts and interactions among 32K LLM agents (called Chirpers) over a year. We start with homophily and social influence among LLMs, learning that similar to humans', their social networks exhibit these fundamental phenomena. Next, we study the toxic language of LLMs, its linguistic features, and their interaction patterns, finding that LLMs show different structural patterns in toxic posting than humans. After studying the ideological leaning in LLMs posts, and the polarization in their community, we focus on how to prevent their potential harmful activities. We present a simple yet effective method, cal...