Literature DB >> 22304165

Clustering drives assortativity and community structure in ensembles of networks.

David V Foster1, Jacob G Foster, Peter Grassberger, Maya Paczuski.   

Abstract

Clustering, assortativity, and communities are key features of complex networks. We probe dependencies between these features and find that ensembles of networks with high clustering display both high assortativity by degree and prominent community structure, while ensembles with high assortativity show much less enhancement of the clustering or community structure. Further, clustering can amplify a small homophilic bias for trait assortativity in network ensembles. This marked asymmetry suggests that transitivity could play a larger role than homophily in determining the structure of many complex networks.

Year:  2011        PMID: 22304165     DOI: 10.1103/PhysRevE.84.066117

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


  10 in total

1.  Design and characterization of chemical space networks for different compound data sets.

Authors:  Magdalena Zwierzyna; Martin Vogt; Gerald M Maggiora; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2014-12-03       Impact factor: 3.686

2.  Comparison of bioactive chemical space networks generated using substructure- and fingerprint-based measures of molecular similarity.

Authors:  Bijun Zhang; Martin Vogt; Gerald M Maggiora; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2015-06-07       Impact factor: 3.686

3.  Quantifying randomness in real networks.

Authors:  Chiara Orsini; Marija M Dankulov; Pol Colomer-de-Simón; Almerima Jamakovic; Priya Mahadevan; Amin Vahdat; Kevin E Bassler; Zoltán Toroczkai; Marián Boguñá; Guido Caldarelli; Santo Fortunato; Dmitri Krioukov
Journal:  Nat Commun       Date:  2015-10-20       Impact factor: 14.919

4.  Multiple Lattice Model for Influenza Spreading.

Authors:  Antonella Liccardo; Annalisa Fierro
Journal:  PLoS One       Date:  2015-10-29       Impact factor: 3.240

5.  Predicting language diversity with complex networks.

Authors:  Tomasz Raducha; Tomasz Gubiec
Journal:  PLoS One       Date:  2018-04-27       Impact factor: 3.240

6.  Structure constrained by metadata in networks of chess players.

Authors:  Nahuel Almeira; Ana L Schaigorodsky; Juan I Perotti; Orlando V Billoni
Journal:  Sci Rep       Date:  2017-11-09       Impact factor: 4.379

7.  Cumulative effects of triadic closure and homophily in social networks.

Authors:  Aili Asikainen; Gerardo Iñiguez; Javier Ureña-Carrión; Kimmo Kaski; Mikko Kivelä
Journal:  Sci Adv       Date:  2020-05-08       Impact factor: 14.136

8.  Deciphering the global organization of clustering in real complex networks.

Authors:  Pol Colomer-de-Simón; M Ángeles Serrano; Mariano G Beiró; J Ignacio Alvarez-Hamelin; Marián Boguñá
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

9.  Has large-scale named-entity network analysis been resting on a flawed assumption?

Authors:  Brent D Fegley; Vetle I Torvik
Journal:  PLoS One       Date:  2013-07-24       Impact factor: 3.240

10.  Immunization strategy based on the critical node in percolation transition.

Authors:  Yang Liu; Bo Wei; Zhen Wang; Yong Deng
Journal:  Phys Lett A       Date:  2015-09-16       Impact factor: 2.654

  10 in total

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