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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A general Markov chain approach for disease and rumour spreading in complex networks

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de Arruda, Guilherme Ferraz [1] ; Rodrigues, Francisco Aparecido [1] ; Rodriguez, Pablo Martin [1] ; Cozzo, Emanuele [2, 3] ; Moreno, Yamir [2, 3, 4]
Total Authors: 5
[1] Univ Sao Paulo, Dept Matemat Aplicada & Estat, Inst Ciencias Matemat & Comp, Campus Sao Carlos, Caixa Postal 668, BR-13560970 Sao Carlos, SP - Brazil
[2] Univ Zaragoza, Inst Biocomputat & Phys Complex Syst BIFI, Zaragoza 50018 - Spain
[3] Univ Zaragoza, Dept Theoret Phys, Zaragoza 50018 - Spain
[4] Inst Sci Interchange, Complex Networks & Syst Lagrange Lab, Turin - Italy
Total Affiliations: 4
Document type: Journal article
Source: JOURNAL OF COMPLEX NETWORKS; v. 6, n. 2, p. 215-242, APR 2018.
Web of Science Citations: 5

Spreading processes are ubiquitous in natural and artificial systems. They can be studied via a plethora of models, depending on the specific details of the phenomena under study. Disease contagion and rumour spreading are among the most important of these processes due to their practical relevance. However, despite the similarities between them, current models address both spreading dynamics separately. In this article, we propose a general spreading model that is based on discrete time Markov chains. The model includes all the transitions that are plausible for both a disease contagion process and rumour propagation. We show that our model not only covers the traditional spreading schemes but that it also contains some features relevant in social dynamics, such as apathy, forgetting, and lost/recovering of interest. The model is evaluated analytically to obtain the spreading thresholds and the early time dynamical behaviour for the contact and reactive processes in several scenarios. Comparison with Monte Carlo simulations shows that the Markov chain formalism is highly accurate while it excels in computational efficiency. We round off our work by showing how the proposed framework can be applied to the study of spreading processes occurring on social networks. (AU)

FAPESP's process: 16/25682-5 - Information spreading in complex networks
Grantee:Francisco Aparecido Rodrigues
Support type: Regular Research Grants
FAPESP's process: 15/03868-7 - Asymptotic behavior of stochastic processes on graphs and applications
Grantee:Pablo Martin Rodriguez
Support type: Scholarships abroad - Research
FAPESP's process: 16/11648-0 - Limit theorems and phase transition results for information propagation models on graphs
Grantee:Pablo Martin Rodriguez
Support type: Regular Research Grants
FAPESP's process: 12/25219-2 - Modeling, analysis and simulation of dynamic process on complex networks
Grantee:Guilherme Ferraz de Arruda
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 15/07463-1 - Spreading processes on multilayer networks
Grantee:Guilherme Ferraz de Arruda
Support type: Scholarships abroad - Research Internship - Doctorate