Analysis of the structure of complex networks at different resolution levels

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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 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 ... continued below

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Arenas, A.; Fernandez, A. & Gomez, S. February 28, 2008.

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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 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.

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  • Journal Name: New Journal of Physics

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  • Report No.: LBNL-1446E
  • Grant Number: DE-AC02-05CH11231
  • DOI: 10.1088/1367-2630/10/5/053039 | External Link
  • Office of Scientific & Technical Information Report Number: 946815
  • Archival Resource Key: ark:/67531/metadc897020

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  • February 28, 2008

Added to The UNT Digital Library

  • Sept. 27, 2016, 1:39 a.m.

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  • Nov. 8, 2016, 12:12 p.m.

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Arenas, A.; Fernandez, A. & Gomez, S. Analysis of the structure of complex networks at different resolution levels, article, February 28, 2008; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc897020/: accessed September 20, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.