A clarified typology of core-periphery structure in networks

Core-periphery structure, the arrangement of a network into dense core and sparse periphery, is versatile descriptor various social, biological, technological networks. In practice, different core-periphery algorithms are often applied interchangeably, despite fact that they can yield inconsistent descriptions structure. For example, two most widely used algorithms, k-cores decomposition classic two-block model Borgatti Everett, extract fundamentally structures: latter partitions binary hub-and-spoke layout, while former divides it layered hierarchy. We introduce typology to clarify these differences, along with Bayesian stochastic block modeling techniques classify networks in accordance this typology. Empirically, we find rich diversity structure among Through detailed case study, demonstrate importance acknowledging situating within when conducting domain-specific analyses.