# Evaluating the Simulation of Human Personality-Driven Susceptibility to Misinformation with LLMs

arXiv: https://arxiv.org/abs/2506.23610 · HTML: https://mlsanity.com/paper/2506.23610/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 43 references that are in the map.
- First posted on arXiv 30 Jun 2025.

## Builds on (most cited first, 10 of 10)

- [The Rise and Potential of Large Language Model Based Agents: A Survey](https://mlsanity.com/paper/2309.07864/) (2023)
- [Out of One, Many: Using Language Models to Simulate Human Samples](https://mlsanity.com/paper/2209.06899/) (2022)
- [On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey](https://mlsanity.com/paper/2406.15126/) (2024)
- [LLM Agents in Interaction: Measuring Personality Consistency and Linguistic Alignment in Interacting Populations of Large Language Models](https://mlsanity.com/paper/2402.02896/) (2024)
- [Human and LLM Biases in Hate Speech Annotations: A Socio-Demographic Analysis of Annotators and Targets](https://mlsanity.com/paper/2410.07991/) (2024)
- [AI for social science and social science of AI: A Survey](https://mlsanity.com/paper/2401.11839/) (2024)
- [Open Models, Closed Minds? On Agents Capabilities in Mimicking Human Personalities through Open Large Language Models](https://mlsanity.com/paper/2401.07115/) (2024)
- [Designing AI-Agents with Personalities: A Psychometric Approach](https://mlsanity.com/paper/2410.19238/) (2024)
- [Evaluation of Reliability Criteria for News Publishers with Large Language Models](https://mlsanity.com/paper/2412.15896/) (2024)
- [Exploring the Links between Personality Traits and Suscep;bility to Disinformation](https://mlsanity.com/paper/2108.05150/) (2021)

## Built on by (most cited first, 3 of 3)

- [Population-Aligned Persona Generation for LLM-based Social Simulation](https://mlsanity.com/paper/2509.10127/) (2025)
- [Do Persona-Infused LLMs Affect Performance in a Strategic Reasoning Game?](https://mlsanity.com/paper/2512.06867/) (2025)
- [Belief-Sim: Towards Belief-Driven Simulation of Demographic Misinformation Susceptibility](https://mlsanity.com/paper/2603.03585/) (2026)

## Abstract (arXiv)

Large language models (LLMs) make it possible to generate synthetic behavioural data at scale, offering an ethical and low-cost alternative to human experiments. Whether such data can faithfully capture psychological differences driven by personality traits, however, remains an open question. We evaluate the capacity of LLM agents, conditioned on Big-Five profiles, to reproduce personality-based variation in susceptibility to misinformation, focusing on news discernment, the ability to judge true headlines as true and false headlines as false. Leveraging published datasets in which human participants with known personality profiles rated headline accuracy, we create matching LLM agents and compare their responses to the original human patterns. Certain trait-misinformation associations, notably those involving Agreeableness and Conscientiousness, are reliably replicated, whereas others diverge, revealing systematic biases in how LLMs internalize and express personality. The results underscore both the promise and the limits of personality-aligned LLMs for behavioral simulation, and offer new insight into modeling cognitive diversity in artificial agents.