Agent Heterogeneity Mediates Extremism in an Adaptive Social Network Model
Agent Heterogeneity Mediates Extremism in an Adaptive Social Network Model
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DOI：
10.48550/arxiv.2305.10230
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发表时间：
2023-05
期刊：
影响因子：
--
通讯作者：
S. Bullock;Hiroki Sayama
中科院分区：
文献类型：
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作者：
S. Bullock;Hiroki Sayama
对自适应社交网络上现有的意见动态模型进行扩展，引入更新政策异质性，代表了这样一个事实：社会动物之间的个体差异可以影响它们与其他动物形成社会纽带的倾向，并受到它们与其他动物的社会纽带的影响。在原始模型中，模型代理人群体的意见和社会联系由于三个社会过程而发生变化：一致性，同质性和neophily。然而，在这里，我们探讨的情况下，每个节点的易感性，这三个过程是参数化的节点特定的值独立随机从一些分布。这种异质性的引入增加了最终种群中的极端主义和连通性的程度（相对于可比的同质网络），并导致节点更新策略参数以及节点意见的显着不确定性。每个节点的更新策略参数还预测它们在最终网络配置中将属于的社区的属性。这些结果表明，更新政策的异质性，在社会人口可能有显着的影响，极端主义社区在现实世界中的人口的形成。
An existing model of opinion dynamics on an adaptive social network is extended to introduce update policy heterogeneity, representing the fact that individual differences between social animals can affect their tendency to form, and be influenced by, their social bonds with other animals. As in the original model, the opinions and social connections of a population of model agents change due to three social processes: conformity, homophily and neophily. Here, however, we explore the case in which each node's susceptibility to these three processes is parameterised by node-specific values drawn independently at random from some distribution. This introduction of heterogeneity increases both the degree of extremism and connectedness in the final population (relative to comparable homogeneous networks) and leads to significant assortativity with respect to node update policy parameters as well as node opinions. Each node's update policy parameters also predict properties of the community that they will belong to in the final network configuration. These results suggest that update policy heterogeneity in social populations may have a significant impact on the formation of extremist communities in real-world populations.