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Polarization and Belief Dynamics in the Black and White Communities: An Agent-Based Network Model from the Data

机译:极化和信仰动力学黑白社区:从数据的代理网络为基础的模型

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摘要

Public health care interventions—regarding vaccination, obesity, and HIV, for example—standardly take the form of information dissemination across a community. But information networks can vary importantly between different ethnic communities, as can levels of trust in information from different sources. We use data from the Greater Pittsburgh Random Household Health Survey to construct models of information networks for White and Black communities--models which reflect the degree of information contact between individuals, with degrees of trust in information from various sources correlated with positions in that social network. With simple assumptions regarding belief change and social reinforcement, we use those modeled networks to build dynamic agent-based models of how information can be expected to flow and how beliefs can be expected to change across each community. With contrasting information from governmental and religious sources, the results show importantly different dynamic patterns of belief polarization within the two communities.
机译:公共卫生干预措施 - 关于疫苗接种,肥胖和艾滋病毒,例如,标准采取社区信息传播的形式。但信息网络可以在不同的民族社区之间重要各种各样,与不同来源的信息的信任程度一样。我们使用大型匹兹堡随机家庭健康调查的数据来构建用于白色和黑色社区的信息网络模型 - 反映各个人物之间的信息接触程度的模型,各种来源的信息中的信任程度与社交中的职位相关联网络。通过对信仰变化和社会强化的简单假设,我们使用这些建模网络来构建基于动态代理的模型,这些模型如何如何流动,以及如何在每个社区中改变如何改变信息。通过政府和宗教来源的对比信息,结果表明了两个社区内的重要信念极化的不同动态模式。

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