Articles producció científica> Enginyeria Informàtica i Matemàtiques

Clustering determines the dynamics of complex contagions in multiplex networks

  • Identification data

    Identifier: PC:2546
    Authors:
    Alex ArenasYong ZhuangOsman Yagan
    Abstract:
    DOI: 10.1103/PhysRevE.95.012312 URL: http://journals.aps.org/pre/abstract/10.1103/PhysRevE.95.012312 Filiació URV: SI Inclòs a la memòria: SI
  • Others:

    Author, as appears in the article.: Alex Arenas; Yong Zhuang; Osman Yagan
    Department: Enginyeria Informàtica i Matemàtiques
    URV's Author/s: ARENAS MORENO, ALEJANDRO; Yong Zhuang; Osman Yagan
    Keywords: Multiplexing Dynamics Complex networks
    Abstract: We present the mathematical analysis of generalized complex contagions in a class of clustered multiplex networks. The model is intended to understand spread of influence, or any other spreading process implying a threshold dynamics, in setups of interconnected networks with significant clustering. The contagion is assumed to be general enough to account for a content-dependent linear threshold model, where each link type has a different weight (for spreading influence) that may depend on the content (e.g., product, rumor, political view) that is being spread. Using the generating functions formalism, we determine the conditions, probability, and expected size of the emergent global cascades. This analysis provides a generalization of previous approaches and is especially useful in problems related to spreading and percolation. The results present nontrivial dependencies between the clustering coefficient of the networks and its average degree. In particular, several phase transitions are shown to occur depending on these descriptors. Generally speaking, our findings reveal that increasing clustering decreases the probability of having global cascades and their size, however, this tendency changes with the average degree. There exists a certain average degree from which on clustering favors the probability and size of the contagion. By comparing the dynamics of complex contagions over multiplex networks and their monoplex projections, we demonstrate that ignoring link types and aggregating network layers may lead to inaccurate conclusions about contagion dynamics, particularly when the correlation of degrees between layers is high.
    Research group: Algorithms embedded in Physical Systems
    Thematic Areas: Computer engineering Ingeniería informática Enginyeria informàtica
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 1539-3755
    Author identifier: 0000-0003-0937-0334; n/a; n/a
    Record's date: 2017-02-08
    Journal volume: 95
    Papper version: info:eu-repo/semantics/acceptedVersion
    Link to the original source: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.95.012312
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.1103/PhysRevE.95.012312
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2017
    First page: Art.num. 012312
    Publication Type: Article Artículo Article
  • Keywords:

    Anàlisi matemàtica
    Xarxes complexes
    Multiplexing
    Dynamics
    Complex networks
    Computer engineering
    Ingeniería informática
    Enginyeria informàtica
    1539-3755
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