Literature DB >> 35639738

backbone: An R package to extract network backbones.

Zachary P Neal1.   

Abstract

Networks are useful for representing phenomena in a broad range of domains. Although their ability to represent complexity can be a virtue, it is sometimes useful to focus on a simplified network that contains only the most important edges: the backbone. This paper introduces and demonstrates a substantially expanded version of the backbone package for R, which now provides methods for extracting backbones from weighted networks, weighted bipartite projections, and unweighted networks. For each type of network, fully replicable code is presented first for small toy examples, then for complete empirical examples using transportation, political, and social networks. The paper also demonstrates the implications of several issues of statistical inference that arise in backbone extraction. It concludes by briefly reviewing existing applications of backbone extraction using the backbone package, and future directions for research on network backbone extraction.

Entities:  

Year:  2022        PMID: 35639738      PMCID: PMC9154188          DOI: 10.1371/journal.pone.0269137

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.752


  23 in total

1.  Emergence of scaling in random networks

Authors: 
Journal:  Science       Date:  1999-10-15       Impact factor: 47.728

2.  Assessing experimentally derived interactions in a small world.

Authors:  Debra S Goldberg; Frederick P Roth
Journal:  Proc Natl Acad Sci U S A       Date:  2003-04-03       Impact factor: 11.205

3.  Fuzzy communities and the concept of bridgeness in complex networks.

Authors:  Tamás Nepusz; Andrea Petróczi; László Négyessy; Fülöp Bazsó
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2008-01-18

4.  Extracting the multiscale backbone of complex weighted networks.

Authors:  M Angeles Serrano; Marián Boguñá; Alessandro Vespignani
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-08       Impact factor: 11.205

5.  Information filtering in complex weighted networks.

Authors:  Filippo Radicchi; José J Ramasco; Santo Fortunato
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2011-04-01

6.  Nonparametric sparsification of complex multiscale networks.

Authors:  Nicholas J Foti; James M Hughes; Daniel N Rockmore
Journal:  PLoS One       Date:  2011-02-08       Impact factor: 3.240

7.  Extracting h-Backbone as a Core Structure in Weighted Networks.

Authors:  Ronda J Zhang; H Eugene Stanley; Fred Y Ye
Journal:  Sci Rep       Date:  2018-09-25       Impact factor: 4.379

8.  Identifying hidden coalitions in the US House of Representatives by optimally partitioning signed networks based on generalized balance.

Authors:  Samin Aref; Zachary P Neal
Journal:  Sci Rep       Date:  2021-10-07       Impact factor: 4.379

9.  Comparing alternatives to the fixed degree sequence model for extracting the backbone of bipartite projections.

Authors:  Zachary P Neal; Rachel Domagalski; Bruce Sagan
Journal:  Sci Rep       Date:  2021-12-14       Impact factor: 4.379

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  1 in total

1.  On network backbone extraction for modeling online collective behavior.

Authors:  Carlos Henrique Gomes Ferreira; Fabricio Murai; Ana P C Silva; Martino Trevisan; Luca Vassio; Idilio Drago; Marco Mellia; Jussara M Almeida
Journal:  PLoS One       Date:  2022-09-15       Impact factor: 3.752

  1 in total

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