Proceedings of the Annual Meeting of the Cognitive Science Society

Conspiracy theories cover topics from politicians to worldevents. Frequently, proponents of conspiracies hold thesebeliefs strongly despite available evidence that may challengeor disprove them. Therefore, conspiratorial reasoning hasoften been described as illegitimate or flawed. In the paper,we explore the possibility of growing a rational (Bayesian)conspiracy theorist through an Agent-Based Model. The agenthas reasonable constraints on access to the total informationas well its access to the global population.The model shows that network structures are central tomaintain objectively mistaken beliefs. Increasing the size ofthe available network yielded increased confidence inmistaken beliefs and subsequent network pruning, allowingfor belief purism. Rather than ameliorating and correctingmistaken beliefs (where agents move toward the correctmean), large networks appear to maintain and strengthenthem. As such, large networks may increase the potential forbelief polarization, extreme beliefs, and conspiratorialthinking – even amongst Bayesian agents.