You Can't Fool Us: Understanding the Resilience of LLM-driven Agent Communities to Misinformation
For researchers studying misinformation dynamics, this provides a mechanistic understanding of how psychological traits and interventions shape community-level resilience.
This paper uses LLM-based agent simulations to study how communities with varying levels of Actively Open-minded Thinking (AOT) and Political Ideology (PI) respond to misinformation. It finds that higher AOT improves resistance and recovery, while moderate ideologies recover more reliably than polarized ones, with interventions like persuasion and fact-checking being most effective for post-peak correction.
Misinformation resilience is a dynamic community process: communities differ not only in whether they initially trust false claims, but also in how they recover through interaction, questioning, correction, and support withdrawal. We study this process with an LLM-based agent simulation that constructs synthetic communities along two theoretically motivated dimensions: Actively Open-minded Thinking (AOT), which captures evidence-seeking and willingness to revise beliefs, and Political Ideology (PI), which captures identity-based interpretation of contested claims. These two traits allow us to examine how evidence-oriented reasoning and ideological alignment jointly shape community responses to credible misinformation shocks. Across systematically varied AOT-PI communities, we find that higher AOT improves both resistance to misinformation uptake and recovery after trust peaks. PI shapes the recovery pathway: ideologically moderate communities recover more reliably, while polarized communities retain more residual support. Stance-level analysis shows that resilience depends on whether agents move from questioning a claim to denying or correcting it and withdrawing prior support. Intervention experiments further show that persuasion and fact checking better support post-peak correction, whereas accuracy prompts mainly induce early caution and source warnings have weaker effects. Together, this work provides a mechanism-level account of community misinformation resilience, showing how psychological composition and intervention design shape whether communities move from misinformation exposure toward correction or persistent support.