Literature DB >> 20365725

Zero Pearson coefficient for strongly correlated growing trees.

S N Dorogovtsev1, A L Ferreira, A V Goltsev, J F F Mendes.   

Abstract

We obtained Pearson's coefficient of strongly correlated recursive networks growing by preferential attachment of every new vertex by m edges. We found that the Pearson coefficient is exactly zero in the infinite network limit for the recursive trees (m=1). If the number of connections of new vertices exceeds one (m>1), then the Pearson coefficient in the infinite networks equals zero only when the degree distribution exponent gamma does not exceed 4. We calculated the Pearson coefficient for finite networks and observed a slow power-law-like approach to an infinite network limit. Our findings indicate that Pearson's coefficient strongly depends on size and details of networks, which makes this characteristic virtually useless for quantitative comparison of different networks.

Mesh:

Year:  2010        PMID: 20365725     DOI: 10.1103/PhysRevE.81.031135

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


  2 in total

1.  Factors determining nestedness in complex networks.

Authors:  Samuel Jonhson; Virginia Domínguez-García; Miguel A Muñoz
Journal:  PLoS One       Date:  2013-09-19       Impact factor: 3.240

2.  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

  2 in total

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