Collective Opinion Dynamics in Structured LLM Populations
Large Language Models are increasingly deployed as interacting agents in settings such as online platforms, recommendation systems, and multi-agent applications. Understanding the collective behaviors that emerge from their interactions is therefore increasingly crucial, especially as these behaviors may shape public opinion and contribute to polarization. In this work, we investigate how network structure and group composition shape the evolution of opinions in populations of LLM agents engaged in multi-round debates. We generate networks with controlled levels of homophily and varying group sizes, and perform ten independent runs per configuration. The results show that LLM agents exhib...
| Authors | Erica Cau, Andrea Failla, Giulio Rossetti |
|---|---|
| Primary category | cs.SI |
| Published | 13 April 2026 |
| Last updated at source | 28 September 2026 |
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