Analysis of the structure of complex networks at different resolution levels

Simple item page
dc.creatorArenas, Alex
dc.creatorFernandez, Alberto
dc.creatorGomez, Sergio
dc.date2007-03-23
dc.date2008-01-15
dc.date.accessioned2026-07-07T09:41:25Z
dc.date.available2026-07-07T09:41:25Z
dc.descriptionModular structure is ubiquitous in real-world complex networks, and its detection is important because it gives insights in the structure-functionality Modular structure is ubiquitous in real-world complex networks, and its detection is important because it gives insights in the structure-functionality relationship. The standard approach is based on the optimization of a quality function, modularity, which is a relative quality measure for a partition of a network into modules. Recently some authors [1,2] have pointed out that the optimization of modularity has a fundamental drawback: the existence of a resolution limit beyond which no modular structure can be detected even though these modules might have own entity. The reason is that several topological descriptions of the network coexist at different scales, which is, in general, a fingerprint of complex systems. Here we propose a method that allows for multiple resolution screening of the modular structure. The method has been validated using synthetic networks, discovering the predefined structures at all scales. Its application to two real social networks allows to find the exact splits reported in the literature, as well as the substructure beyond the actual split.
dc.description23 pages, 5 figures
dc.identifierhttps://arxiv.org/abs/physics/0703218
dc.identifierhttp://arxiv.org/abs/physics/0703218
dc.identifierNew J. Phys. 10 (2008) 053039
dc.identifierdoi:10.1088/1367-2630/10/5/053039
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/161821
dc.subjectData Analysis, Statistics and Probability
dc.subjectOther Condensed Matter
dc.subjectDiscrete Mathematics
dc.subjectPhysics and Society
dc.subjectQuantitative Methods
dc.titleAnalysis of the structure of complex networks at different resolution levels
dc.typetext

Files

Collections

arXiv