Autor según el artículo: Alex Arenas; Yong Zhuang; Osman Yagan

Departamento: Enginyeria Informàtica i Matemàtiques

Autor/es de la URV: ARENAS MORENO, ALEJANDRO; Yong Zhuang; Osman Yagan

Palabras clave: Multiplexing Dynamics Complex networks

Resumen: We present the mathematical analysis of generalized complex contagions in a class of clustered multiplex networks. The model is intended to understand spread of influence, or any other spreading process implying a threshold dynamics, in setups of interconnected networks with significant clustering. The contagion is assumed to be general enough to account for a content-dependent linear threshold model, where each link type has a different weight (for spreading influence) that may depend on the content (e.g., product, rumor, political view) that is being spread. Using the generating functions formalism, we determine the conditions, probability, and expected size of the emergent global cascades. This analysis provides a generalization of previous approaches and is especially useful in problems related to spreading and percolation. The results present nontrivial dependencies between the clustering coefficient of the networks and its average degree. In particular, several phase transitions are shown to occur depending on these descriptors. Generally speaking, our findings reveal that increasing clustering decreases the probability of having global cascades and their size, however, this tendency changes with the average degree. There exists a certain average degree from which on clustering favors the probability and size of the contagion. By comparing the dynamics of complex contagions over multiplex networks and their monoplex projections, we demonstrate that ignoring link types and aggregating network layers may lead to inaccurate conclusions about contagion dynamics, particularly when the correlation of degrees between layers is high.

Grupo de investigación: Algorithms embedded in Physical Systems

Áreas temáticas: Computer engineering Ingeniería informática Enginyeria informàtica

Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/

ISSN: 1539-3755

Identificador del autor: 0000-0003-0937-0334; n/a; n/a

Fecha de alta del registro: 2017-02-08

Volumen de revista: 95

Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion

Enlace a la fuente original: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.95.012312

DOI del artículo: 10.1103/PhysRevE.95.012312

Entidad: Universitat Rovira i Virgili

Año de publicación de la revista: 2017

Página inicial: Art.num. 012312

Tipo de publicación: Article Artículo Article