Hyperbolicity measures democracy in real-world networks

被引:22
|
作者
Borassi, Michele [1 ]
Chessa, Alessandro [1 ,2 ]
Caldarelli, Guido [1 ,3 ,4 ]
机构
[1] IMT Inst Adv Studies, I-55100 Lucca, Italy
[2] Linkalab, Complex Syst Computat Lab, I-09129 Cagliari, Italy
[3] Ist Sistemi Complessi, I-00185 Rome, Italy
[4] London Inst Math Sci, London W1K 2XF, England
关键词
GROMOV-HYPERBOLICITY; CONGESTION;
D O I
10.1103/PhysRevE.92.032812
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
In this work, we analyze the hyperbolicity of real-world networks, a geometric quantity that measures if a space is negatively curved. We provide two improvements in our understanding of this quantity: first of all, in our interpretation, a hyperbolic network is "aristocratic", since few elements "connect" the system, while a non-hyperbolic network has a more "democratic" structure with a larger number of crucial elements. The second contribution is the introduction of the average hyperbolicity of the neighbors of a given node. Through this definition, we outline an "influence area" for the vertices in the graph. We show that in real networks the influence area of the highest degree vertex is small in what we define "local" networks (i.e., social or peer-to-peer networks), and large in "global" networks (i.e., power grid, metabolic networks, or autonomous system networks).
引用
收藏
页数:6
相关论文
共 50 条
  • [1] On Computing the Hyperbolicity of Real-World Graphs
    Borassi, Michele
    Coudert, David
    Crescenzi, Pierluigi
    Marino, Andrea
    [J]. ALGORITHMS - ESA 2015, 2015, 9294 : 215 - 226
  • [2] On the relationships between topological measures in real-world networks
    Jamakovic, Almerima
    Uhlig, Steve
    [J]. NETWORKS AND HETEROGENEOUS MEDIA, 2008, 3 (02) : 345 - 359
  • [3] Hyperfiniteness of Real-World Networks
    Honda, Yutaro
    Inoue, Yoshitaka
    Ito, Hiro
    Sasajima, Munehiko
    Teruyama, Junichi
    Uno, Yushi
    [J]. REVIEW OF SOCIONETWORK STRATEGIES, 2019, 13 (02): : 123 - 141
  • [4] Hyperfiniteness of Real-World Networks
    Yutaro Honda
    Yoshitaka Inoue
    Hiro Ito
    Munehiko Sasajima
    Junichi Teruyama
    Yushi Uno
    [J]. The Review of Socionetwork Strategies, 2019, 13 : 123 - 141
  • [5] The statistical physics of real-world networks
    Giulio Cimini
    Tiziano Squartini
    Fabio Saracco
    Diego Garlaschelli
    Andrea Gabrielli
    Guido Caldarelli
    [J]. Nature Reviews Physics, 2019, 1 : 58 - 71
  • [6] The statistical physics of real-world networks
    Cimini, Giulio
    Squartini, Tiziano
    Saracco, Fabio
    Garlaschelli, Diego
    Gabrielli, Andrea
    Caldarelli, Guido
    [J]. NATURE REVIEWS PHYSICS, 2019, 1 (01) : 58 - 71
  • [7] Neural networks in real-world applications
    Knoblock, C
    [J]. IEEE EXPERT-INTELLIGENT SYSTEMS & THEIR APPLICATIONS, 1996, 11 (04): : 4 - 4
  • [8] Spatial growth of real-world networks
    Kaiser, M
    Hilgetag, CC
    [J]. PHYSICAL REVIEW E, 2004, 69 (03) : 036103 - 1
  • [9] Leaders in communities of real-world networks
    Fu, Jingcheng
    Wu, Jianliang
    Liu, Chuanjian
    Xu, Jin
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2016, 444 : 428 - 441
  • [10] Small-World Features of Real-World Networks
    Xiao, Wenjun
    Li, Meisheng
    Chen, Guanrong
    [J]. JOURNAL OF COMMUNICATIONS AND NETWORKS, 2017, 19 (03) : 291 - 297