Macro- and mesoscale pattern interdependencies in complex networks

Identifying and explaining the structure of complex networks at different scales has become an important problem across disciplines. At the mesoscale, modular architecture has attracted most of the attention. At the macroscale, other arrangements-e.g. nestedness or core-periphery-have been studied i...

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Detalles Bibliográficos
Autores: Palazzi Nieves, Maria José, Borge-Holthoefer, Javier, Tessone, Claudio J., Solé-Ribalta, Albert
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Institución:Universitat Oberta de Catalunya (UOC)
Repositorio:O2, repositorio institucional de la UOC
OAI Identifier:oai:openaccess.uoc.edu:10609/124286
Acceso en línea:http://hdl.handle.net/10609/124286
Access Level:acceso abierto
Palabra clave:complex networks
mesoscale
nestedness
modularity
ecological networks
xarxes ecològiques
xarxes complexes
mesoscala
modularitat
anidament
redes complejas
mesoescala
modularidad
anidamiento
redes ecológicas
Algorithms
Algorismes
Algoritmos
Descripción
Sumario:Identifying and explaining the structure of complex networks at different scales has become an important problem across disciplines. At the mesoscale, modular architecture has attracted most of the attention. At the macroscale, other arrangements-e.g. nestedness or core-periphery-have been studied in parallel, but to a much lesser extent. However, empirical evidence increasingly suggests that characterizing a network with a unique pattern typology may be too simplistic, since a system can integrate properties from distinct organizations at different scales. Here, we explore the relationship between some of these different organizational patterns: two at the mesoscale (modularity and in-block nestedness); and one at the macroscale (nestedness). We show experimentally and analytically that nestedness imposes bounds to modularity, with exact analytical results in idealized scenarios. Specifically, we show that nestedness and modularity are interdependent. Furthermore, we analytically evidence that in-block nestedness provides a natural combination between nested and modular networks, taking structural properties of both. Far from a mere theoretical exercise, understanding the boundaries that discriminate each architecture is fundamental, to the extent that modularity and nestedness are known to place heavy dynamical effects on processes, such as species abundances and stability in ecology.