The $\textit{Silicon Society}$ Cookbook: Design Space of LLM-based Social Simulations

2026-04-30

AI Summary

This study addresses the lack of systematic investigation into the design space of large language model (LLM)-based social simulations, which hinders the assessment of simulation fidelity. It reveals for the first time that this design space exhibits a nontrivial geometric structure. Through systematic analysis of key design choices—including base LLM type and agent connectivity patterns—and their interaction effects, the work identifies the base LLM as the dominant factor shaping simulation outcomes. While some parameters exert additive effects, others engage in complex interactions. Integrating LLM-based agent modeling, social network topology, and survey-validated opinion alignment among agents, this research provides a reproducible design framework for constructing realistic and trustworthy silicon-based societies.

Abstract

Studies attempting to simulate human behavior with $\textit{Silicon Societies}$ grow in numbers while LLM-only social networks have started appearing outside of controlled settings. However, the design space of these networks remains under-studied, which contributes to a gap in validating model realism. To enable future works to make more informed design decisions, we perform a systematic analysis of the consequences and interactions of key design choices in simulated social networks, including the choice of base model used to model individual agents, and how they are connected to each other. Using surveys as a proxy for agent opinions, our findings suggest that the geometry of the design space is non-trivial, with some parameters behaving in additive ways while others display more complex interactions. In particular, the choice of the base LLM is the most important variable impacting the simulation outcomes.

Problem

• Silicon Societies
• LLM-based social simulations
• design space
• model realism
• agent-based modeling

Innovation

• LLM-based social simulation
• Silicon Societies
• design space analysis
• agent-based modeling
• model realism