首页> 外文会议>International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation >Modeling Belief Divergence and Opinion Polarization with Bayesian Networks and Agent-Based Simulation A Study on Traditional Healing Use in South Africa
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Modeling Belief Divergence and Opinion Polarization with Bayesian Networks and Agent-Based Simulation A Study on Traditional Healing Use in South Africa

机译:用贝叶斯网络和基于代理的模拟对信念分歧和意见极化进行建模:南非传统治疗方法的研究

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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.
机译:这项研究使用具有人类居住模式的基于代理的模拟来对信念修正和有关医疗保健选择的信息交换进行建模。我们采用基于贝叶斯网络公式的两种最新微观经济学理论来进行个人信念更新,然后研究信念修改过程的宏观影响。该模型试图解释村庄和地区一级的传统治疗方法,同时在个体一级提供具有单一概念性因素流动性的因果机制。所得的模拟结果估计了南非林波波村对传统治疗方法的依赖性,并且该估计值已通过经验数据进行了验证。

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