Literature DB >> 18517702

Robustness of community structure in networks.

Brian Karrer1, Elizaveta Levina, M E J Newman.   

Abstract

The discovery of community structure is a common challenge in the analysis of network data. Many methods have been proposed for finding community structure, but few have been proposed for determining whether the structure found is statistically significant or whether, conversely, it could have arisen purely as a result of chance. In this paper we show that the significance of community structure can be effectively quantified by measuring its robustness to small perturbations in network structure. We propose a suitable method for perturbing networks and a measure of the resulting change in community structure and use them to assess the significance of community structure in a variety of networks, both real and computer generated.

Year:  2008        PMID: 18517702     DOI: 10.1103/PhysRevE.77.046119

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  46 in total

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2.  Prioritizing network communities.

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Authors:  Yunpeng Zhao; Elizaveta Levina; Ji Zhu
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4.  Diffusion on networked systems is a question of time or structure.

Authors:  Jean-Charles Delvenne; Renaud Lambiotte; Luis E C Rocha
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5.  Assessing the robustness of cluster solutions obtained from sparse count matrices.

Authors:  Kathleen M Gates; Zachary F Fisher; Cara Arizmendi; Teague R Henry; Kelly A Duffy; Peter J Mucha
Journal:  Psychol Methods       Date:  2019-02-11

6.  Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD.

Authors:  Damien A Fair; Deepti Bathula; Molly A Nikolas; Joel T Nigg
Journal:  Proc Natl Acad Sci U S A       Date:  2012-04-02       Impact factor: 11.205

7.  Link-Prediction Enhanced Consensus Clustering for Complex Networks.

Authors:  Matthew Burgess; Eytan Adar; Michael Cafarella
Journal:  PLoS One       Date:  2016-05-20       Impact factor: 3.240

8.  Stability of Network Communities as a Function of Task Complexity.

Authors:  Stefan Fuertinger; Kristina Simonyan
Journal:  J Cogn Neurosci       Date:  2016-08-30       Impact factor: 3.225

9.  Mapping change in large networks.

Authors:  Martin Rosvall; Carl T Bergstrom
Journal:  PLoS One       Date:  2010-01-27       Impact factor: 3.240

10.  Functional brain networks develop from a "local to distributed" organization.

Authors:  Damien A Fair; Alexander L Cohen; Jonathan D Power; Nico U F Dosenbach; Jessica A Church; Francis M Miezin; Bradley L Schlaggar; Steven E Petersen
Journal:  PLoS Comput Biol       Date:  2009-05-01       Impact factor: 4.475

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