Título:
Dynamical detection of network communities
Otros títulos:
Coordinador:
Director:
Compilador:
Autor:
Quiles, Marcos G.
Macau, Elbert E. N.
Rubido, Nicolás
Macau, Elbert E. N.
Rubido, Nicolás
Tutor:
Tipo de documento:
Artículo
Editor:
Palabras clave:
Communities
Networks
Particle system
Dynamical proces
Networks
Particle system
Dynamical proces
Descriptores:
Año de publicación:
2016
Contenido:
Resumen:
A prominent feature of complex networks is the appearance of communities, also known as modular structures. Specifically, communities are groups of nodes that are densely connected among each other but connect sparsely with others. However, detecting communities in networks is so far a major challenge, in particular, when networks evolve in time. Here, we propose a change in the community detection approach. It underlies in defining an intrinsic dynamic for the nodes of the network as interacting particles (based on diffusive equations of motion and on the topological properties of the network) that results in a fast convergence of the particle system into clustered patterns. The resulting patterns correspond to the communities of the network. Since our detection of communities is constructed from a dynamical process, it is able to analyse time-varying networks straightforwardly. Moreover, for static networks, our numerical experiments show that our approach achieves similar results as the methodologies currently recognized as the most efficient ones. Also, since our approach defines an N-body problem, it allows for efficient numerical implementations using parallel computations that increase its speed performance.
Descripción:
metadata.articulos.dc.description.uri:
Editorial:
Nature Publishing Group
EN:
Scientific Reports, 2016, 6, art. no. 25570
Financiadores:
Citación:
Quiles, M., Macau, E.E.N., Rubido, N. Dynamical detection of network communities. Scientific Reports, 2016, 6, art. nro. 25570. doi: 10.1038/srep25570
Citación:
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ISBN:
e-ISBN:
ISSN:
2045-2322
ISMN:
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Licencia:
Licencia Creative Commons Atribución (CC –BY 4.0)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| 101038srep25570.pdf | — | 1.88 MB | Adobe PDF |