 WoS ID: 000353703400035 Scopus ID: 2-s2.0-84928563708
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| Ranking in interconnected multilayer networks reveals versatile nodes
Nature Communications 6, 6868 (2015)
M. De Domenico, A. Sole-Ribalta, E. Omodei, S. Gomez, A. Arenas
Keywords: multiplex complex networks centrality complex systems
| Read DOI Abstract |
Real-world complex systems exhibit multiple levels of relationships. In many cases, they require to be modeled by interconnected multilayer networks, characterizing interactions on several levels simultaneously. It is of crucial importance in many fields, from economics to biology, from urban planning to social sciences, to identify the most (or the less) influent nodes in a network. However, defining the centrality of actors in an interconnected structure is not trivial. In this paper, we capitalize on the tensorial formalism, recently proposed to characterize and investigate this kind of complex topologies, to show how several centrality measures -- well-known in the case of standard ("monoplex") networks -- can be extended naturally to the realm of interconnected multiplexes. We consider diagnostics widely used in different fields, e.g., computer science, biology, communication and social sciences, to cite only some of them. We show, both theoretically and numerically, that using the weighted monoplex obtained by aggregating the multilayer network leads, in general, to relevant differences in ranking the nodes by their importance.
The pre-print on the arXiv only partially corresponds to the accepted version of the paper. |