摘要：AbstractMany policy networks are characterized by belief-oriented segregation, where actors with shared belief systems are clustered together and few opportunities exist for communication across coalitions of like-minded stakeholders. This inhibits the ability of network actors to effectively learn about, and successfully manage, complex policy problems. Despite the importance of understanding why these structures emerge, the processes that generate belief polarization in networks are not well-studied. This paper derives a general agent-based model of network formation and belief change from the Advocacy Coalition Framework (ACF), a prominent theory of the policy process that has been widely applied to the study of belief conflict in contentious policy systems. Simulation results suggest that the ACF assumption of biased information processing plays a critical role in the emergence of belief-oriented segregation in networks. This model provides a starting point for re-thinking the role of cognitive bias in social and policy learning, as well as the relationships between belief change and the evolving structure of policy networks.
