We use a data-driven agent-based model to study the core–periphery structure of two collaboration networks, R&D alliances between firms and co-authorship relations between scientists. To characterize the network embeddedness of agents, we introduce a coreness value obtained from a weighted $k$-core decomposition. We study the change of these coreness values when collaborations with newcomers or established agents are formed. Our agent-based model is able to reproduce the empirical coreness differences of collaboration partners and to explain why we observe a change in partner selection for agents with high network embeddedness.

中文翻译：

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网络嵌入对合作伙伴选择的作用：基于代理的经验验证模型

我们使用数据驱动的基于代理的模型来研究两个协作网络的核心-外围结构、公司之间的研发联盟和科学家之间的合着关系。为了表征代理的网络嵌入性，我们引入了从加权获得的核心值$ķ$-核心分解。当与新来者或已建立的代理形成合作时，我们研究了这些核心价值观的变化。我们基于代理的模型能够重现合作伙伴的经验核心差异，并解释为什么我们观察到具有高网络嵌入性的代理的合作伙伴选择发生变化。