Literature DB >> 12731952

Modularity and extreme edges of the internet.

Kasper Astrup Eriksen1, Ingve Simonsen, Sergei Maslov, Kim Sneppen.   

Abstract

We study the spectral properties of a diffusion process taking place on the Internet network focusing on the slowest decaying modes. These modes identify an underlying modular structure roughly corresponding to individual countries. For instance, in the slowest decaying mode the diffusion current flows from Russia to U.S. military sites. Quantitatively the modular structure manifests itself in a 10 times larger participation ratio of its slow decaying modes compared to a random scale-free network. We propose to use the fraction of nodes participating in slow decaying modes as a general measure of the modularity of a network. For the 100 slowest decaying modes of the Internet this fraction is approximately 30%. Finally, we suggest that the degree of isolation of an individual module can be assessed by comparing its participation in different diffusion modes.

Mesh:

Year:  2003        PMID: 12731952     DOI: 10.1103/PhysRevLett.90.148701

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  20 in total

1.  Modularity from fluctuations in random graphs and complex networks.

Authors:  Roger Guimerà; Marta Sales-Pardo; Luís A Nunes Amaral
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2004-08-19

2.  Functional cartography of complex metabolic networks.

Authors:  Roger Guimerà; Luís A Nunes Amaral
Journal:  Nature       Date:  2005-02-24       Impact factor: 49.962

3.  Resolution limit in community detection.

Authors:  Santo Fortunato; Marc Barthélemy
Journal:  Proc Natl Acad Sci U S A       Date:  2006-12-26       Impact factor: 11.205

4.  An information-theoretic framework for resolving community structure in complex networks.

Authors:  Martin Rosvall; Carl T Bergstrom
Journal:  Proc Natl Acad Sci U S A       Date:  2007-04-23       Impact factor: 11.205

5.  A model of Internet topology using k-shell decomposition.

Authors:  Shai Carmi; Shlomo Havlin; Scott Kirkpatrick; Yuval Shavitt; Eran Shir
Journal:  Proc Natl Acad Sci U S A       Date:  2007-06-22       Impact factor: 11.205

Review 6.  Maps of random walks on complex networks reveal community structure.

Authors:  Martin Rosvall; Carl T Bergstrom
Journal:  Proc Natl Acad Sci U S A       Date:  2008-01-23       Impact factor: 11.205

7.  Cartography of complex networks: modules and universal roles.

Authors:  Roger Guimerà; Luís A Nunes Amaral
Journal:  J Stat Mech       Date:  2005-02-01       Impact factor: 2.231

8.  Sick and edgy: walk-counting as a metric of epidemic spreading on networks.

Authors:  Dennis C Wylie; Wayne M Getz
Journal:  J R Soc Interface       Date:  2008-12-16       Impact factor: 4.118

9.  Classes of complex networks defined by role-to-role connectivity profiles.

Authors:  Roger Guimerà; Marta Sales-Pardo; Luís A N Amaral
Journal:  Nat Phys       Date:  2007       Impact factor: 20.034

10.  Resilience of networks with community structure behaves as if under an external field.

Authors:  Gaogao Dong; Jingfang Fan; Louis M Shekhtman; Saray Shai; Ruijin Du; Lixin Tian; Xiaosong Chen; H Eugene Stanley; Shlomo Havlin
Journal:  Proc Natl Acad Sci U S A       Date:  2018-06-20       Impact factor: 11.205

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