Asikainen Aili, Iñiguez Gerardo, Ureña-Carrión Javier, Kaski Kimmo, Kivelä Mikko
Department of Computer Science, School of Science, Aalto University, FI-00076, Finland.
Department of Network and Data Science, Central European University, H-1051 Budapest, Hungary.
Sci Adv. 2020 May 8;6(19):eaax7310. doi: 10.1126/sciadv.aax7310. eCollection 2020 May.
Social network structure has often been attributed to two network evolution mechanisms-triadic closure and choice homophily-which are commonly considered independently or with static models. However, empirical studies suggest that their dynamic interplay generates the observed homophily of real-world social networks. By combining these mechanisms in a dynamic model, we confirm the longheld hypothesis that choice homophily and triadic closure cause induced homophily. We estimate how much observed homophily in friendship and communication networks is amplified due to triadic closure. We find that cumulative effects of homophily amplification can also lead to the widely documented core-periphery structure of networks, and to memory of homophilic constraints (equivalent to hysteresis in physics). The model shows that even small individual bias may prompt network-level changes such as segregation or core group dominance. Our results highlight that individual-level mechanisms should not be analyzed separately without considering the dynamics of society as a whole.
社会网络结构通常归因于两种网络演化机制——三元闭包和选择同质性，这两种机制通常被独立考虑或与静态模型一起考虑。然而，实证研究表明，它们的动态相互作用产生了现实世界社会网络中观察到的同质性。通过在动态模型中结合这些机制，我们证实了长期以来的假设，即选择同质性和三元闭包会导致诱导同质性。我们估计了由于三元闭包，友谊和通信网络中观察到的同质性被放大了多少。我们发现，同质性放大的累积效应也会导致网络中广泛记录的核心-边缘结构，以及对同质性约束的记忆（相当于物理学中的滞后现象）。该模型表明，即使是很小的个体偏差也可能促使网络层面的变化，如隔离或核心群体主导。我们的结果强调，在不考虑整个社会动态的情况下，不应单独分析个体层面的机制。
