Proceedings of the Annual Meeting of the Cognitive Science Society

Belief polarization represents a puzzling and important dynamic in belief updating. There is growing awareness that belief polarization can be Bayesian. We provide pre-registered experimental evidence that beliefs can polarize when people receive conflicting testimony from two groups of sources if they have different beliefs about which group's members have greater independence in terms of the factors which affect their testimony. We show this is predicted by a Bayesian Network model of belief updating.