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Factors Determining Nestedness in Complex Networks

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  • Samuel Jonhson
  • Virginia Domínguez-García
  • Miguel A Muñoz

Abstract

Understanding the causes and effects of network structural features is a key task in deciphering complex systems. In this context, the property of network nestedness has aroused a fair amount of interest as regards ecological networks. Indeed, Bastolla et al. introduced a simple measure of network nestedness which opened the door to analytical understanding, allowing them to conclude that biodiversity is strongly enhanced in highly nested mutualistic networks. Here, we suggest a slightly refined version of such a measure of nestedness and study how it is influenced by the most basic structural properties of networks, such as degree distribution and degree-degree correlations (i.e. assortativity). We find that most of the empirically found nestedness stems from heterogeneity in the degree distribution. Once such an influence has been discounted – as a second factor – we find that nestedness is strongly correlated with disassortativity and hence – as random networks have been recently found to be naturally disassortative – they also tend to be naturally nested just as the result of chance.

Suggested Citation

  • Samuel Jonhson & Virginia Domínguez-García & Miguel A Muñoz, 2013. "Factors Determining Nestedness in Complex Networks," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-7, September.
  • Handle: RePEc:plo:pone00:0074025
    DOI: 10.1371/journal.pone.0074025
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    Cited by:

    1. Wandelt, Sebastian & Sun, Xiaoqian & Menasalvas, Ernestina & Rodríguez-González, Alejandro & Zanin, Massimiliano, 2019. "On the use of random graphs as null model of large connected networks," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 318-325.
    2. Michel Alexandre & Felipe Jordão Xavier & Thiago Christiano Silva & Francisco A. Rodrigues, 2022. "Nestedness in the Brazilian Financial System," Working Papers Series 566, Central Bank of Brazil, Research Department.
    3. Shimada, Takashi & Ogushi, Fumiko & Török, János & Kertész, János & Kaski, Kimmo, 2023. "A simple model of edit activity in Wikipedia," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    4. Fabio Saracco & Riccardo Di Clemente & Andrea Gabrielli & Luciano Pietronero, 2015. "From Innovation to Diversification: A Simple Competitive Model," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-19, November.
    5. Fabio Saracco & Riccardo Di Clemente & Andrea Gabrielli & Tiziano Squartini, 2015. "Detecting early signs of the 2007-2008 crisis in the world trade," Papers 1508.03533, arXiv.org, revised Jul 2016.
    6. Zhuo-Ming Ren & An Zeng & Yi-Cheng Zhang, 2020. "Bridging nestedness and economic complexity in multilayer world trade networks," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-8, December.

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