Autor segons l'article: Alex Arenas; Yong Zhuang; Osman Yagan
Departament: Enginyeria Informàtica i Matemàtiques
Autor/s de la URV: ARENAS MORENO, ALEJANDRO; Yong Zhuang; Osman Yagan
Paraules clau: Multiplexing Dynamics Complex networks
Resum: 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.
Grup de recerca: Algorithms embedded in Physical Systems
Àrees temàtiques: Computer engineering Ingeniería informática Enginyeria informàtica
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 1539-3755
Identificador de l'autor: 0000-0003-0937-0334; n/a; n/a
Data d'alta del registre: 2017-02-08
Volum de revista: 95
Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2017
Pàgina inicial: Art.num. 012312
Tipus de publicació: Article Artículo Article
Repositori URV