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Fast and accurate determination of modularity and its effect size

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Treviño, Santiago, Nyberg, Amy, Del Genio, Charo I. and Bassler, Kevin E. (2015) Fast and accurate determination of modularity and its effect size. Journal of Statistical Mechanics : Theory and Experiment, 2015 (2). P02003. doi:10.1088/1742-5468/2015/02/P02003 ISSN 1742-5468.

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Official URL: http://dx.doi.org/10.1088/1742-5468/2015/02/P02003

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Abstract

We present a fast spectral algorithm for community detection in complex networks. Our method searches for the partition with the maximum value of the modularity via the interplay of several refinement steps that include both agglomeration and division. We validate the accuracy of the algorithm by applying it to several real-world benchmark networks. On all these, our algorithm performs as well or better than any other known polynomial scheme. This allows us to extensively study the modularity distribution in ensembles of Erdős–Rényi networks, producing theoretical predictions for means and variances inclusive of finite-size corrections. Our work provides a way to accurately estimate the effect size of modularity, providing a z-score measure of it and enabling a more informative comparison of networks with different numbers of nodes and links.

Item Type: Journal Article
Subjects: Q Science > QC Physics
Divisions: Faculty of Science, Engineering and Medicine > Research Centres > Centre for Complexity Science
Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- )
Faculty of Science, Engineering and Medicine > Science > Mathematics
Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School
Library of Congress Subject Headings (LCSH): Algorithms, Statistical mechanics
Journal or Publication Title: Journal of Statistical Mechanics : Theory and Experiment
Publisher: Institute of Physics Publishing Ltd.
ISSN: 1742-5468
Official Date: 3 February 2015
Dates:
DateEvent
3 February 2015Published
3 January 2015Accepted
30 June 2014Submitted
Volume: 2015
Number: 2
Article Number: P02003
DOI: 10.1088/1742-5468/2015/02/P02003
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 18 November 2016
Date of first compliant Open Access: 18 November 2016
Funder: National Science Foundation (U.S.) (NSF), United States. Air Force. Office of Scientific Research (AFOSR), United States. Defense Advanced Research Projects Agency (DARPA), Seventh Framework Programme (European Commission) (FP7)
Grant number: DMR-1206839 (NSF), FA9550-12-1- 0405 (AFOSR & DARPA), 288021 (FP7)

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