Emergence of network features from multiplexity
By Alessio Cardillo, Jesús Gómez-Gardeñes, Massimiliano Zanin, Miguel Romance, David Papo, Francisco del Pozo, Stefano Boccaletti. Scientific Reports, 2012
520 citations recorded by the source corpus.
Many biological and man-made networked systems are characterized by the simultaneous presence of different sub-networks organized in separate layers, with links and nodes of qualitatively different types. While during the past few years theoretical studies have examined a variety of structural features of complex networks, the outstanding question is whether such features are characterizing all single layers, or rather emerge as a result of coarse-graining, i.e. when going from the multilayered to the aggregate network representation. Here we address this issue with the help of real data. We analyze the structural properties of an intrinsically multilayered real network, the European Air Transportation Multiplex Network in which each commercial airline defines a network layer. We examine how several structural measures evolve as layers are progressively merged together. In particular, we discuss how the topology of each layer affects the emergence of structural properties in the aggregate network.
Subfields: Ecology, Evolution, Behavior and Systematics, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/2c2ff76b98100fc6d6cd33c566c29fe730cc1cc3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Ecology, Evolution, Behavior and Systematics
In Statistical and Nonlinear Physics
- M. A. Porter
- Alex Arenas
- Manlio De Domenico
- Santo Fortunato
- Marinka Zitnik
- Yamir Moreno
- Marc Barthelemy
- Sergio Gómez
Citations in the corpus
- Learning Structural Node Embeddings via Diffusion Wavelets (2017, background): “We consider six airlines operating flights between European airports [2]: 4 commercial (Air France, Easyjet, Lufthansa, and RyanAir) and 2 cargo airlines (TAP Portugal, and European Airline Transport).”
- Ranking in interconnected multilayer networks reveals versatile nodes (2013, background): “Here, the network is built from flight routes operated by 37 different air companies (layers) between 450 European airports (nodes) [1].”
- Multilayer networks (2013, methodology): “In this example, the layers that correspond to low-cost airlines have qualitatively different properties from those that correspond to major airlines [75].”