Modularity with a more accurate baseline model

Journal Article (2025)
Author(s)

B.L. Chang (TU Delft - Network Architectures and Services)

P.F.A. Van Mieghem (TU Delft - Network Architectures and Services)

Research Group
Network Architectures and Services
DOI related publication
https://doi.org/10.1103/PhysRevE.111.044317
More Info
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Publication Year
2025
Language
English
Research Group
Network Architectures and Services
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
4
Volume number
111
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Abstract

We derive an expression for the exact probability Pr[i∼j] of a link between a node i with degree di and a node j with degree dj in a graph belonging to the class of Erdos-Rényi G(N,L) random graphs with N nodes and L links. The probability Pr[i∼j] is commonly approximated as didj2L and appears in the formula of Newman's modularity, which plays a crucial rule in community detection in networks. We show that, when applied to graphs not belonging to the class of Erdos-Rényi random graphs, our formula for Pr[i∼j] is considerably more accurate than didj2L and leads to the detection of different clusters or partitions than the original modularity formula.

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