Literature DB >> 16803279

Scale-free network growth by ranking.

Santo Fortunato1, Alessandro Flammini, Filippo Menczer.   

Abstract

Network growth is currently explained through mechanisms that rely on node prestige measures, such as degree or fitness. In many real networks, those who create and connect nodes do not know the prestige values of existing nodes but only their ranking by prestige. We propose a criterion of network growth that explicitly relies on the ranking of the nodes according to any prestige measure, be it topological or not. The resulting network has a scale-free degree distribution when the probability to link a target node is any power-law function of its rank, even when one has only partial information of node ranks. Our criterion may explain the frequency and robustness of scale-free degree distributions in real networks, as illustrated by the special case of the Web graph.

Year:  2006        PMID: 16803279     DOI: 10.1103/PhysRevLett.96.218701

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


  16 in total

1.  Topical interests and the mitigation of search engine bias.

Authors:  S Fortunato; A Flammini; F Menczer; A Vespignani
Journal:  Proc Natl Acad Sci U S A       Date:  2006-08-10       Impact factor: 11.205

2.  Likelihood-based approach to discriminate mixtures of network models that vary in time.

Authors:  Naomi A Arnold; Raul J Mondragón; Richard G Clegg
Journal:  Sci Rep       Date:  2021-03-04       Impact factor: 4.379

3.  Popularity versus similarity in growing networks.

Authors:  Fragkiskos Papadopoulos; Maksim Kitsak; M Ángeles Serrano; Marián Boguñá; Dmitri Krioukov
Journal:  Nature       Date:  2012-09-12       Impact factor: 49.962

4.  Activity driven modeling of time varying networks.

Authors:  N Perra; B Gonçalves; R Pastor-Satorras; A Vespignani
Journal:  Sci Rep       Date:  2012-06-25       Impact factor: 4.379

5.  Structural and dynamical patterns on online social networks: the Spanish May 15th movement as a case study.

Authors:  Javier Borge-Holthoefer; Alejandro Rivero; Iñigo García; Elisa Cauhé; Alfredo Ferrer; Darío Ferrer; David Francos; David Iñiguez; María Pilar Pérez; Gonzalo Ruiz; Francisco Sanz; Fermín Serrano; Cristina Viñas; Alfonso Tarancón; Yamir Moreno
Journal:  PLoS One       Date:  2011-08-19       Impact factor: 3.240

6.  Political audience diversity and news reliability in algorithmic ranking.

Authors:  Saumya Bhadani; Shun Yamaya; Alessandro Flammini; Filippo Menczer; Giovanni Luca Ciampaglia; Brendan Nyhan
Journal:  Nat Hum Behav       Date:  2022-02-03

7.  Digital Ecology: Coexistence and Domination among Interacting Networks.

Authors:  Kaj-Kolja Kleineberg; Marián Boguñá
Journal:  Sci Rep       Date:  2015-05-19       Impact factor: 4.379

8.  Intermediate Levels of Network Heterogeneity Provide the Best Evolutionary Outcomes.

Authors:  Flávio L Pinheiro; Dominik Hartmann
Journal:  Sci Rep       Date:  2017-11-10       Impact factor: 4.379

9.  Modeling statistical properties of written text.

Authors:  M Angeles Serrano; Alessandro Flammini; Filippo Menczer
Journal:  PLoS One       Date:  2009-04-29       Impact factor: 3.240

10.  Competition between global and local online social networks.

Authors:  Kaj-Kolja Kleineberg; Marián Boguñá
Journal:  Sci Rep       Date:  2016-04-27       Impact factor: 4.379

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