Autor según el artículo: Albert Solé-Ribalta; Manlio De Domenico; Sergio Gómez; Alex Arenas
Departamento: Enginyeria Informàtica i Matemàtiques
Autor/es de la URV: SOLÉ RIBALTA, ALBERT; DE DOMENICO ., MANLIO; GÓMEZ JIMÉNEZ, SERGIO; ARENAS MORENO, ALEJANDRO
Palabras clave: Centrality Multilayer complex networks Random walks
Resumen: Real-world complex systems exhibit multiple levels of relationships. In many cases they require to be modeled as interconnected multilayer networks, characterizing interactions of several types simultaneously. It is of crucial importance in many fields, from economics to biology and from urban planning to social sciences, to identify the most (or the less) influent nodes in a network using centrality measures. However, defining the centrality of actors in interconnected complex networks is not trivial. In this paper, we rely on the tensorial formalism recently proposed to characterize and investigate this kind of complex topologies, and extend two well known random walk centrality measures, the random walk betweenness and closeness centrality, to interconnected multilayer networks. For each of the measures we provide analytical expressions that completely agree with numerically results.
Grupo de investigación: Algorithms embedded in Physical Systems
Áreas temáticas: Enginyeria informàtica Ingeniería informática Computer engineering
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 0167-2789
Identificador del autor: 0000-0003-3474-7594; 0000-0001-5158-8594; 0000-0003-1820-0062; 0000-0003-0937-0334
Fecha de alta del registro: 2016-05-31
Página final: 79
Volumen de revista: 323-324
Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
Enlace a la fuente original: https://www.sciencedirect.com/science/article/abs/pii/S0167278916000026?via%3Dihub
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
DOI del artículo: 10.1016/j.physd.2016.01.002
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2016
Página inicial: 73
Tipo de publicación: Article Artículo Article