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Cited by 330

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Size reduction of complex networks preserving modularity

Open access
Arenas, A, Duch, J, Fernández, A, Gómez, S·2007·New Journal of Physics

Abstract

The ubiquity of modular structure in real-world complex networks is the focus of attention in many trials to understand the interplay between network topology and functionality. The best approaches to the identification of modular structure are based on the optimization of a quality function known as modularity . However this optimization is a hard task provided that the computational complexity of the problem is in the non-deterministic polynomial-time hard (NP-hard) class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining their modularity. This size reduction allows use of heuristic algorithms that optimize modularity for a better exploration of the modularity landscape. We compare the modularity obtained in several real complex-networks by using the extremal optimization algorithm, before and after the size reduction, showing the improvement obtained. We speculate that the proposed analytical size reduction could be extended to an exact coarse graining of the network in the scope of real-space renormalization.

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Metadata

Authors
Arenas, A., Duch, J., Fernández, A., & Gómez, S.
Venue
New Journal of Physics
Published
2007-06-28
Volume
9
Issue
6
Pages
176-176
ISSN
1367-2630 (ISSN-L)
OpenAlex
W2130776740
Cited by
330
References
3
FWCI
11.12
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Size reduction of complex networks preserving modularity. https://app.cochat.ai/papers/10.1088/1367-2630/9/6/176
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Arenas, A., Duch, J., Fernández, A., & Gómez, S. (2007). Size reduction of complex networks preserving modularity. New Journal of Physics. https://doi.org/10.1088/1367-2630/9/6/176

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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