File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Identifying hubs in directed networks

TitleIdentifying hubs in directed networks
Authors
Issue Date20-Mar-2024
PublisherAmerican Physical Society
Citation
Physical Review E, 2024, v. 109, n. 3 How to Cite?
Abstract

Nodes in networks that exhibit high connectivity, also called “hubs,” play a critical role in determining the structural and functional properties of networked systems. However, there is no clear definition of what constitutes a hub node in a network, and the classification of network hubs in existing work has either been purely qualitative or relies on ad hoc criteria for thresholding continuous data that do not generalize well to networks with certain degree sequences. Here we develop a set of efficient nonparametric methods that classify hub nodes in directed networks using the Minimum Description Length principle, effectively providing a clear and principled definition for network hubs. We adapt our methods to both unweighted and weighted networks, and we demonstrate them in a range of example applications using real and synthetic network data. 


Persistent Identifierhttp://hdl.handle.net/10722/342103
ISSN
2023 Impact Factor: 2.2
2023 SCImago Journal Rankings: 0.805
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorKirkley, Alec William-
dc.date.accessioned2024-04-02T08:25:35Z-
dc.date.available2024-04-02T08:25:35Z-
dc.date.issued2024-03-20-
dc.identifier.citationPhysical Review E, 2024, v. 109, n. 3-
dc.identifier.issn2470-0045-
dc.identifier.urihttp://hdl.handle.net/10722/342103-
dc.description.abstract<p>Nodes in networks that exhibit high connectivity, also called “hubs,” play a critical role in determining the structural and functional properties of networked systems. However, there is no clear definition of what constitutes a hub node in a network, and the classification of network hubs in existing work has either been purely qualitative or relies on ad hoc criteria for thresholding continuous data that do not generalize well to networks with certain degree sequences. Here we develop a set of efficient nonparametric methods that classify hub nodes in directed networks using the Minimum Description Length principle, effectively providing a clear and principled definition for network hubs. We adapt our methods to both unweighted and weighted networks, and we demonstrate them in a range of example applications using real and synthetic network data.<span> </span></p>-
dc.languageeng-
dc.publisherAmerican Physical Society-
dc.relation.ispartofPhysical Review E-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleIdentifying hubs in directed networks-
dc.typeArticle-
dc.identifier.doi10.1103/PhysRevE.109.034310-
dc.identifier.scopuseid_2-s2.0-85188435957-
dc.identifier.volume109-
dc.identifier.issue3-
dc.identifier.eissn2470-0053-
dc.identifier.isiWOS:001195834800002-
dc.identifier.issnl2470-0045-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats