Literature DB >> 11735891

Critical behavior of propagation on small-world networks.

D H Zanette1.   

Abstract

We report numerical evidence that an epidemiclike model, which can be interpreted as the propagation of a rumor, exhibits critical behavior at a finite randomness of the underlying small-world network. The transition occurs between a regime where the rumor "dies" in a small neighborhood of its origin, and a regime where it spreads over a finite fraction of the whole population. Critical exponents are evaluated through finite-size scaling analysis, and the dependence of the critical randomness with the network connectivity is studied. The behavior of this system as a function of the small-network randomness bears noticeable similarities with an epidemiological model reported recently [M. Kuperman and G. Abramson, Phys. Rev. Lett. 86, 2909 (2001)], in spite of substantial differences in the respective dynamical rules.

Mesh:

Year:  2001        PMID: 11735891     DOI: 10.1103/PhysRevE.64.050901

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  11 in total

1.  Epidemic spreading in complex networks.

Authors:  Jie Zhou; Zong-Hua Liu
Journal:  Front Phys China       Date:  2008-07-08

2.  A Dissemination Model Based on Psychological Theories in Complex Social Networks.

Authors:  Tianyi Luo; Zhidong Cao; Daniel Zeng; Qingpeng Zhang
Journal:  IEEE Trans Cogn Dev Syst       Date:  2021-01-19       Impact factor: 4.546

3.  Spread mechanism and control strategy of social network rumors under the influence of COVID-19.

Authors:  Hongwen Hui; Chengcheng Zhou; Xing Lü; Jiarong Li
Journal:  Nonlinear Dyn       Date:  2020-08-10       Impact factor: 5.022

4.  Dynamic Analysis and Optimal Control of Rumor Spreading Model with Recurrence and Individual Behaviors in Heterogeneous Networks.

Authors:  Xinru Tong; Haijun Jiang; Xiangyong Chen; Shuzhen Yu; Jiarong Li
Journal:  Entropy (Basel)       Date:  2022-03-27       Impact factor: 2.738

5.  Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations.

Authors:  Áron R Perez-Lopez; Kristóf Z Szalay; Dénes Türei; Dezső Módos; Katalin Lenti; Tamás Korcsmáros; Peter Csermely
Journal:  Sci Rep       Date:  2015-05-11       Impact factor: 4.379

6.  Immunization against the Spread of Rumors in Homogenous Networks.

Authors:  Laijun Zhao; Jiajia Wang; Rongbing Huang
Journal:  PLoS One       Date:  2015-05-01       Impact factor: 3.240

7.  Emergence of blind areas in information spreading.

Authors:  Zi-Ke Zhang; Chu-Xu Zhang; Xiao-Pu Han; Chuang Liu
Journal:  PLoS One       Date:  2014-04-24       Impact factor: 3.240

8.  Numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks.

Authors:  Panpan Shu; Wei Wang; Ming Tang; Younghae Do
Journal:  Chaos       Date:  2015-06       Impact factor: 3.642

9.  The spread and control of rumors in a multilingual environment.

Authors:  Shuzhen Yu; Zhiyong Yu; Haijun Jiang; Xuehui Mei; Jiarong Li
Journal:  Nonlinear Dyn       Date:  2020-04-27       Impact factor: 5.022

10.  Risk estimation of infectious diseases determines the effectiveness of the control strategy.

Authors:  Haifeng Zhang; Jie Zhang; Ping Li; Michael Small; Binghong Wang
Journal:  Physica D       Date:  2011-02-10       Impact factor: 2.300

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