Dokumentdetails
ID
oai:arXiv.org:2406.19953
Thema
Physics - Physics and Society Computer Science - Artificial Inte...Autor
Ansari, Imran Yadav, Pawanesh Sahni, NiteeshKategorie
Computer Science
Jahr
2024
Auflistungsdatum
03.07.2024
Schlüsselwörter
hyperbolic models structure core-peripheryZusammenfassung
The hyperbolic network models exhibit very fundamental and essential features, like small-worldness, scale-freeness, high-clustering coefficient, and community structure.
In this paper, we comprehensively explore the presence of an important feature, the core-periphery structure, in the hyperbolic network models, which is often exhibited by real-world networks.
We focused on well-known hyperbolic models such as popularity-similarity optimization model (PSO) and S1/H2 models and studied core-periphery structures using a well-established method that is based on standard random walk Markov chain model.
The observed core-periphery centralization values indicate that the core-periphery structure can be very pronounced under certain conditions.
We also validate our findings by statistically testing for the significance of the observed core-periphery structure in the network geometry.
This study extends network science and reveals core-periphery insights applicable to various domains, enhancing network performance and resiliency in transportation and information systems.
Ansari, Imran,Yadav, Pawanesh,Sahni, Niteesh, 2024, Uncovering the hidden core-periphery structure in hyperbolic networks
Uncovering the hidden core-periphery structure in hyperbolic networks
hyperbolic models structure core-periphery
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