mlsanityData to 7 Oct 2026

From Heard to Lived Opinions: Simulating Opinion Dynamics with Grounded LLM Agents in Economic Environments

arXiv 2603.26701 ↗First posted 17 Mar 2026physics.soc-ph cs.CYcited by 0

On the map: LLM agents and tool use → Social simulation and multi-agent debate

Abstract (arXiv)

Opinion dynamics (OD) studies how individual opinions evolve and generate collective patterns such as consensus and polarization. While recent work explores OD using populations of LLM-based agents focusing on opinion exchange, it typically does not incorporate individuals' lived experiences, such as economic outcomes of past decisions, which play a critical role in shaping opinions. We propose a novel OD simulation framework that grounds LLM-based agents in an economic environment, allowing them to act and receive environmental feedback. Our simulations exhibit coherent OD at both individual and population levels: individual opinions follow structured trajectories shaped by economic experiences, with adverse conditions inducing opinion rigidity, while at the population level, collective opinions co-move with economic conditions, with inequality amplifying polarization and price instability driving larger distributional shifts. These results highlight the importance of grounding LLM-based agents in environments to capture collective OD.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 8 of its 29 references that are in the map. First posted on arXiv 17 Mar 2026.

Builds on

8 of 29 references.

Closest ancestors · 4

Same direction, newest first

  1. 2025AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society12 Feb
  2. 2023Simulating Opinion Dynamics with Networks of LLM-based Agents16 Nov
  3. 2023EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic Activities16 Oct
  4. 2023Generative Agents: Interactive Simulacra of Human Behavior7 Apr

Other references · 4

  1. 2024The Llama 3 Herd of Modelscited by 14,192
  2. 2020MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformerscited by 1,414
  3. 2025Language-Driven Opinion Dynamics in Agent-Based Simulations with LLMscited by 12
  4. 2025Agent-Based Simulation of a Financial Market with Large Language Modelscited by 6

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2024On the Principles behind Opinion Dynamics in Multi-Agent Systems of Large Language Models
  2. 2025DEBATE: A Large-Scale Benchmark for Evaluating Opinion Dynamics in Role-Playing LLM Agents
  3. 2026Bayesian Belief Layer for Controllable Opinion Dynamics in LLM Agents
  4. 2026ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles
  5. 2025Disentangling Interaction and Bias Effects in Opinion Dynamics of Large Language Models
  6. 2026Physics of Agents: Statistical Mechanics Predicts Collective Behavior of AI Agents
  7. 2026Emergence of Biased Consensus in Multi-Agent LLM Debates
  8. 2025Competing LLM Agents in a Non-Cooperative Game of Opinion Polarisation