Articles producció científica> Enginyeria Informàtica i Matemàtiques

Interplay between k -core and community structure in complex networks

  • Identification data

    Identifier: imarina:8263208
    Authors:
    Malvestio ICardillo AMasuda N
    Abstract:
    © 2020, The Author(s). The organisation of a network in a maximal set of nodes having at least k neighbours within the set, known as k-core decomposition, has been used for studying various phenomena. It has been shown that nodes in the innermost k-shells play a crucial role in contagion processes, emergence of consensus, and resilience of the system. It is known that the k-core decomposition of many empirical networks cannot be explained by the degree of each node alone,or equivalently, random graph models that preserve the degree of each node (i.e., configuration model). Here we study the k-core decomposition of some empirical networks as well as that of some randomised counterparts, and examine the extent to which the k-shell structure of the networks can be accounted for by the community structure.We find that preserving the community structure in the randomisation process is crucial for generating networks whose k-core decomposition is close to the empirical one. We also highlight the existence, in some networks, of a concentration of the nodes in the innermost k-shells into a small number of communities.
  • Others:

    Author, as appears in the article.: Malvestio I; Cardillo A; Masuda N
    Department: Enginyeria Informàtica i Matemàtiques
    URV's Author/s: Cardillo, Alessio Vincenzo
    Keywords: Organization Models Graphs Decomposition
    Abstract: © 2020, The Author(s). The organisation of a network in a maximal set of nodes having at least k neighbours within the set, known as k-core decomposition, has been used for studying various phenomena. It has been shown that nodes in the innermost k-shells play a crucial role in contagion processes, emergence of consensus, and resilience of the system. It is known that the k-core decomposition of many empirical networks cannot be explained by the degree of each node alone,or equivalently, random graph models that preserve the degree of each node (i.e., configuration model). Here we study the k-core decomposition of some empirical networks as well as that of some randomised counterparts, and examine the extent to which the k-shell structure of the networks can be accounted for by the community structure.We find that preserving the community structure in the randomisation process is crucial for generating networks whose k-core decomposition is close to the empirical one. We also highlight the existence, in some networks, of a concentration of the nodes in the innermost k-shells into a small number of communities.
    Thematic Areas: Zootecnia / recursos pesqueiros Saúde coletiva Química Psicología Odontología Nutrição Multidisciplinary sciences Multidisciplinary Medicina veterinaria Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Letras / linguística Interdisciplinar Geografía Geociências Farmacia Engenharias iv Engenharias iii Engenharias ii Enfermagem Educação física Educação Economia Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência de alimentos Ciência da computação Biotecnología Biodiversidade Astronomia / física
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: alessio.cardillo@urv.cat
    Record's date: 2021-10-10
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.nature.com/articles/s41598-020-71426-8
    Papper original source: Scientific Reports. 10 (1):
    APA: Malvestio I; Cardillo A; Masuda N (2020). Interplay between k -core and community structure in complex networks. Scientific Reports, 10(1), -. DOI: 10.1038/s41598-020-71426-8
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.1038/s41598-020-71426-8
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2020
    Publication Type: Journal Publications
  • Keywords:

    Multidisciplinary,Multidisciplinary Sciences
    Organization
    Models
    Graphs
    Decomposition
    Zootecnia / recursos pesqueiros
    Saúde coletiva
    Química
    Psicología
    Odontología
    Nutrição
    Multidisciplinary sciences
    Multidisciplinary
    Medicina veterinaria
    Medicina iii
    Medicina ii
    Medicina i
    Materiais
    Matemática / probabilidade e estatística
    Letras / linguística
    Interdisciplinar
    Geografía
    Geociências
    Farmacia
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Enfermagem
    Educação física
    Educação
    Economia
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência de alimentos
    Ciência da computação
    Biotecnología
    Biodiversidade
    Astronomia / física
  • Documents:

  • Cerca a google

    Search to google scholar