Can LLMs Emulate Human Belief Dynamics?

Fuente: arXiv
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Bibliographic Details
Main Authors: Proma, Adiba Mahbub, Pate, Neeley, Druckman, James N., Ghoshal, Gourab, He, Hangfeng, Hoque, Ehsan
Format: Preprint
Published: 2026
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author Proma, Adiba Mahbub
Pate, Neeley
Druckman, James N.
Ghoshal, Gourab
He, Hangfeng
Hoque, Ehsan
author_facet Proma, Adiba Mahbub
Pate, Neeley
Druckman, James N.
Ghoshal, Gourab
He, Hangfeng
Hoque, Ehsan
contents Can LLMs simulate how humans form and change beliefs in social networks? We put this to the test by replicating an established study on belief dynamics, evaluating 12 LLMs across multiple model families and parameter sizes. The answer is a clear no, and in systematic ways. LLMs fail to capture initial human belief distributions and tend to be overall more conformist than humans, shifting their responses to align with those around them. They also take a nuanced approach to emulating human homophilic tendencies within networks. Our findings carry a double payoff: they highlight fundamental properties of LLM behavior, and they raise a sharp warning against deploying LLMs as human proxies in social simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2605_18781
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Can LLMs Emulate Human Belief Dynamics?
Proma, Adiba Mahbub
Pate, Neeley
Druckman, James N.
Ghoshal, Gourab
He, Hangfeng
Hoque, Ehsan
Social and Information Networks
Artificial Intelligence
Computers and Society
Can LLMs simulate how humans form and change beliefs in social networks? We put this to the test by replicating an established study on belief dynamics, evaluating 12 LLMs across multiple model families and parameter sizes. The answer is a clear no, and in systematic ways. LLMs fail to capture initial human belief distributions and tend to be overall more conformist than humans, shifting their responses to align with those around them. They also take a nuanced approach to emulating human homophilic tendencies within networks. Our findings carry a double payoff: they highlight fundamental properties of LLM behavior, and they raise a sharp warning against deploying LLMs as human proxies in social simulations.
title Can LLMs Emulate Human Belief Dynamics?
topic Social and Information Networks
Artificial Intelligence
Computers and Society
url https://arxiv.org/abs/2605.18781