Ranking in interconnected multilayer networks reveals versatile nodes
By Manlio De Domenico, Albert Solé-Ribalta, E. Omodei, Sergio Gómez, Alex Arenas. 2013
408 citations recorded by the source corpus.
The determination of the most central agents in complex networks is important because they are responsible for a faster propagation of information, epidemics, failures and congestion, among others. A challenging problem is to identify them in networked systems characterized by different types of interactions, forming interconnected multilayer networks. Here we describe a mathematical framework that allows us to calculate centrality in such networks and rank nodes accordingly, finding the ones that play the most central roles in the cohesion of the whole structure, bridging together different types of relations. These nodes are the most versatile in the multilayer network. We investigate empirical interconnected multilayer networks and show that the approaches based on aggregating—or neglecting—the multilayer structure lead to a wrong identification of the most versatile nodes, overestimating the importance of more marginal agents and demonstrating the power of versatility in predicting their role in diffusive and congestion processes. A challenging problem is to identify the most central agents in interconnected multilayer networks. Here, De Domenico et al. present a mathematical framework to calculate centrality in such networks—versatility—and rank nodes accordingly.
Subfields: Experimental and Cognitive Psychology, Statistical and Nonlinear Physics
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In Experimental and Cognitive Psychology
In Statistical and Nonlinear Physics
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Citations in the corpus
- The science of science: from the perspective of complex systems (2017, background): “Issues include the centrality measures [460], community detection [461], structural reducibility [462], and coupled dynamics (e.”
- Random walks and diffusion on networks (2016, background): “By considering RWs on multilayer and temporal networks, one can also generalize such notions of centrality [240, 251, 280–285].”
- The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives (2024, background): “Despite a continuous development of metrics to characterize such a network of networks (Battiston et al., 2014; De Domenico et al., 2015; Nicosia and Latora, 2015; Iacovacci and Bianconi, 2016; Ghariblou et al., 2017; Mandke et al., 2018; Tudisco et al., 2018; Zaoli et al., 2021), applications in…”