Tuning the overlap and the cross-layer correlations in two-layer networks : application to an SIR model with awareness dissemination

Web of Science: 4 cites, Scopus: 4 cites, Google Scholar: cites,

(Universitat de Girona. Departament d'Informàtica, Matemàtica Aplicada i Estadística)
Saldaña, Joan

(Universitat de Girona. Departament d'Informàtica, Matemàtica Aplicada i Estadística)

Data:	2018
Resum:	We study the properties of the potential overlap between two networks A,B sharing the same set of N nodes (a two-layer network) whose respective degree distributions p_A(k), p_B(k) are given. Defining the overlap coefficient as the Jaccard index, we prove that is very close to 0 when A and B are random and independently generated. We derive an upper bound _M for the maximum overlap coefficient permitted in terms of p_A(k), p_B(k) and N. Then we present an algorithm based on cross-rewiring of links to obtain a two-layer network with any prescribed inside the range (0,_M). A refined version of the algorithm allows us to minimize the cross-layer correlations that unavoidably appear for values of beyond a critical overlap _c<_M. Finally, we present a very simple example of an SIR epidemic model with information dissemination and use the algorithms to determine the impact of the overlap on the final outbreak size predicted by the model.
Ajuts:	Ministerio de Economía y Competitividad MTM2017-86795-C3-1-P Ministerio de Economía y Competitividad MTM2014-52402-C3-3-P Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-1617 Agència de Gestió d'Ajuts Universitaris i de Recerca 2014/SGR-1083
Drets:	Tots els drets reservats.
Llengua:	Anglès
Document:	Article ; recerca ; Versió acceptada per publicar
Publicat a:	Physical review E, Vol. 97, issue 3 (March 2018) , art. 32303, ISSN 2470-0045

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Registre creat el 2018-11-12, darrera modificació el 2022-03-27