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This paper employs an agent-based simulation to conceptualize misinformation as a commons problem, framing trust as a collective resource and attention as a limited budget. The findings reveal that shifts in aggregate attention towards low-credibility content lead to a degradation of the trust environment, complicating the processing and correction of credible information. The model identifies four distinct modes of information dynamics鈥攃redible stability, misinformation dominance, polarization, and a mixed baseline鈥攅ach with unique implications for trust trajectories and network structures, highlighting the critical balance between trust repair and harm in policy interventions.
Shifts in attention to low-credibility content can erode societal trust, making credible information increasingly difficult to discern and correct.
Misinformation often harms society not just by spreading a single false belief, but by breaking down the shared trust people rely on to evaluate what is true. This paper presents an agent-based simulation that frames trust as a collective resource and attention as a scarce private budget: when aggregate attention shifts toward low credibility content, the trust environment degrades, making credible information harder to process and correct. Across experiments, the model produces four recurring modes: credible stability, misinformation dominance, polarization, and a mixed baseline, with distinct signatures in trust trajectories and network structure. The results separate two control problems that matter for simulation-based policy exploration: the balance of trust repair versus harm largely determines whether the system recovers or collapses, while homophily and rewiring determine whether disagreement remains integrated or separates into persistent clusters. This foundation provides a transparent testbed for comparative experiments on interventions that must address both trust restoration and structural conditions for cross-cutting exposure.
