Modeling Belief Divergence and Opinion Polarization with Bayesian Networks and Agent-Based Simulation

Abstract

This study uses agent-based simulation with human settlement patterns to model belief revision and information exchange about health care options. We adopt two recent microeconomic theories based on Bayesian Network formulations for individual belief update then examine the macro-level effects of the belief revision process. This model tries to explain traditional healing usage at the village and regional level while providing a causal mechanism with a single conceptual factor, mobility, at the individual level. The resulting simulation estimates the dependency on traditional healing in villages in Limpopo, South Africa, and the estimates are validated with empirical data.