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• W3138995405 abstract "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." @default.
• W3138995405 created "2021-03-29" @default.
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• W3138995405 date "2021-03-19" @default.
• W3138995405 modified "2023-10-02" @default.
• W3138995405 title "A clarified typology of core-periphery structure in networks" @default.
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• W3138995405 doi "https://doi.org/10.1126/sciadv.abc9800" @default.
• W3138995405 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7968838" @default.
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• W3138995405 hasPublicationYear "2021" @default.
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