The structure and dynamics of multilayer networks

Stefano Boccaletti, Ginestra Bianconi, Regino Criado, Charo del Genio, Jesús Gómez-Gardeñes, Miguel Romance, Irene Sendiña-Nadal, Zheng Wang, Massimiliano Zanin

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    2331 Citations (Scopus)
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    Abstract

    In the past years, network theory has successfully characterized the interaction among the constituents of a variety of complex systems, ranging from biological to technological, and social systems. However, up until recently, attention was almost exclusively given to networks in which all components were treated on equivalent footing, while neglecting all the extra information about the temporal- or context-related properties of the interactions under study. Only in the last years, taking advantage of the enhanced resolution in real data sets, network scientists have directed their interest to the multiplex character of real-world systems, and explicitly considered the time-varying and multilayer nature of networks. We offer here a comprehensive review on both structural and dynamical organization of graphs made of diverse relationships (layers) between its constituents, and cover several relevant issues, from a full redefinition of the basic structural measures, to understanding how the multilayer nature of the network affects processes and dynamics.
    Original languageEnglish
    Pages (from-to)1
    JournalPhysics Reports
    Volume544
    Issue number1
    Early online date10 Jul 2014
    DOIs
    Publication statusPublished - 1 Nov 2014

    Bibliographical note

    NOTICE: this is the author’s version of a work that was accepted for publication in Physics Reports. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Physics Reports, Vol 544, (2014) DOI: 10.1016/j.physrep.2014.07.001

    © 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

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