Global decomposition of networks into multiple cores formed by local hubs

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Hauptverfasser: Jeong, Wonhee, Yu, Unjong, Lee, Sang Hoon
Format: Preprint
Veröffentlicht: 2024
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author Jeong, Wonhee
Yu, Unjong
Lee, Sang Hoon
author_facet Jeong, Wonhee
Yu, Unjong
Lee, Sang Hoon
contents Networks are ubiquitous in various fields, representing systems where nodes and their interconnections constitute their intricate structures. We introduce a network decomposition scheme to reveal multiscale core-periphery structures lurking inside, using the concept of locally defined nodal hub centrality and edge-pruning techniques built upon it. We demonstrate that the hub-centrality-based edge pruning reveals a series of breaking points in network decomposition, which effectively separates a network into its backbone and shell structures. Our local-edge decomposition method iteratively identifies and removes locally least connected nodes, and uncovers an onion-like hierarchical structure as a result. Compared with the conventional $k$-core decomposition method, our method based on relative information residing in local structures exhibits a clear advantage in terms of discovering locally crucial substructures. As an application of the method, we present a scheme to detect multiple core-periphery structures and the decomposition of coarse-grained supernode networks, by combining the method with the network community detection.
format Preprint
id arxiv_https___arxiv_org_abs_2407_00355
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Global decomposition of networks into multiple cores formed by local hubs
Jeong, Wonhee
Yu, Unjong
Lee, Sang Hoon
Physics and Society
Statistical Mechanics
Social and Information Networks
Networks are ubiquitous in various fields, representing systems where nodes and their interconnections constitute their intricate structures. We introduce a network decomposition scheme to reveal multiscale core-periphery structures lurking inside, using the concept of locally defined nodal hub centrality and edge-pruning techniques built upon it. We demonstrate that the hub-centrality-based edge pruning reveals a series of breaking points in network decomposition, which effectively separates a network into its backbone and shell structures. Our local-edge decomposition method iteratively identifies and removes locally least connected nodes, and uncovers an onion-like hierarchical structure as a result. Compared with the conventional $k$-core decomposition method, our method based on relative information residing in local structures exhibits a clear advantage in terms of discovering locally crucial substructures. As an application of the method, we present a scheme to detect multiple core-periphery structures and the decomposition of coarse-grained supernode networks, by combining the method with the network community detection.
title Global decomposition of networks into multiple cores formed by local hubs
topic Physics and Society
Statistical Mechanics
Social and Information Networks
url https://arxiv.org/abs/2407.00355