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Agent-basedmodeling approach for group polarization behavior considering conformity and network relationship strength

机译:考虑符合性和网络关系强度的基于代理的基于分区方法

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Currently, group behaviors happen frequently with the development of network technology. As a typical social group behavior, group polarization has been attracted more and more academic attention due to its significant disturbance to public's daily lives. At present, the classic J-A (proposed by Jager and Amblard) and D-W (proposed by Deffuant and Weisbuch) models are used to analyze group polarization process. However, the main shortcomings existing in these models are that the individuals' psychology and their network relationships are rarely considered. In order to overcome the limitations, this article integrates the influence factors such as conformity and network relationship strength integrated into the polarization model. Besides, the BA (proposed by Barabasi and Albert) network model is used as the agent adjacency model due to its closer to the real social network structure. Subsequently, the experimental simulations are carried out with the multi-agent Monte-Carlo method so as to testify the efficiency and effectiveness. The results indicate that different information interaction modes have essential influence on group attitude polarization. Moreover, conformity parameters and the intensity of relationship have dual impacts on both speeding up and slowing down the polarization process.
机译:目前,群体行为经常发生网络技术的发展。由于典型的社会群体行为,由于对公众日常生活的显着干扰,群体极化被吸引了越来越多的学术关注。目前,经典J-A(由Jager和Amblard提出)和D-W(由Deffuant和Weisbuch提出)模型用于分析组极化过程。然而,这些模型中存在的主要缺点是人们很少考虑个人的心理学及其网络关系。为了克服局限性,本文集成了集成到极化模型中的符合性和网络关系强度等影响因素。此外,由于其较近真实的社交网络结构,BA(Barabasi和Albert)网络模型用作代理邻接模型。随后,使用多剂Monte-Carlo方法进行实验模拟,以证明效率和有效性。结果表明,不同的信息相互作用模式对组姿态极化具有重要影响。此外,符合性参数和关系的强度对加速和减慢偏振过程的双重影响。

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