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.

翻译：现有自适应社会网络上的观点动态模型被扩展以引入更新策略异质性，这反映了社会性个体之间的差异会影响其形成社会纽带并受其他动物社会纽带影响的倾向。与原模型一致，模型智能体的观点和社会联系因三种社会过程而改变：从众、同质性和新奇寻求。然而，本文探索了每个节点对这三种过程的敏感性由从某分布中独立随机抽取的节点特定值参数化的情况。这种异质性的引入（相对于同质网络）增加了最终群体中的极端主义程度和连接性，并导致节点更新策略参数及节点观点上的显著同配性。每个节点的更新策略参数还可预测其在最终网络配置中所属社区的性质。这些结果表明，社会群体中的更新策略异质性可能对现实世界中极端主义社区的形成产生显著影响。