网络中的核心结构类型
A Clarified Typology of Core-Periphery Structure in Networks
摘要：
核心-外围结构，即网络由密集的核心和稀疏的外围组成，是各种社会、生物和技术网络的通用描述符。在实践中，不同的核心-外围算法经常被互换地应用，尽管它们可以产生不一致的核心-外围结构描述。例如，两种最广泛使用的算法，k核分解和Borgatti和Everett的经典两块模型，提取了根本不同的结构：后者将网络划分为二进制轴辐式布局，而前者将其划分为分层层次结构。我们引入了一个核心-外围类型来澄清这些差异，以及贝叶斯随机块建模技术来根据这种类型对网络进行分类。从经验上看，网络的核心-外围结构具有丰富的多样性。通过一个详细的案例研究，我们证明了承认这种多样性和定位网络的核心-外围类型学进行特定领域的分析时的重要性。
英文摘要：
Core-periphery structure, the arrangement of a network into a dense core and sparse periphery, is a versatile descriptor of various social, biological, and technological networks. In practice, different core-periphery algorithms are often applied interchangeably, despite the fact that they can yield inconsistent descriptions of core-periphery structure. For example, two of the most widely used algorithms, the k-cores decomposition and the classic two-block model of Borgatti and Everett, extract fundamentally different structures: the latter partitions a network into a binary hub-and-spoke layout, while the former divides it into a layered hierarchy. We introduce a core-periphery typology to clarify these differences, along with Bayesian stochastic block modeling techniques to classify networks in accordance with this typology. Empirically, we find a rich diversity of core-periphery structure among networks. Through a detailed case study, we demonstrate the importance of acknowledging this diversity and situating networks within the core-periphery typology when conducting domain-specific analyses.
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