Giscard, Pierre-Louis and Wilson, Richard Charles orcid.org/0000-0001-7265-3033 (2018) A centrality measure for cycles and subgraphs II. Applied Network Science. ISSN 2364-8228
Abstract
In a recent work we introduced a measure of importance for groups of vertices in a complex network. This centrality for groups is always between 0 and 1 and induces the eigenvector centrality over vertices. Furthermore, its value over any group is the fraction of all network flows intercepted by this group. Here we provide the rigorous mathematical constructions underpinning these results via a semi-commutative extension of a number theoretic sieve. We then established further relations between the eigenvector centrality and the centrality proposed here, showing that the latter is a proper extension of the former to groups of nodes. We finish by comparing the centrality proposed here with the notion of group-centrality introduced by Everett and Borgatti on two real-world networks: the Wolfe’s dataset and the protein-protein interaction network of the yeast Saccharomyces cerevisiae. In this latter case, we demonstrate that the centrality is able to distinguish protein complexes
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2018. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 13 Jun 2018 09:20 |
Last Modified: | 16 Oct 2024 14:49 |
Published Version: | https://doi.org/10.1007/s41109-018-0064-5 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1007/s41109-018-0064-5 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:132002 |
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Filename: 10.1007_2Fs41109_018_0064_5.pdf
Description: A centrality measure for cycles and subgraphs II
Licence: CC-BY 2.5