English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/18030
Share/Impact:
Statistics
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:
Title

Highly clustered scale-free networks

AuthorsKlemm, Konstantin ; Eguíluz, Víctor M.
Issue Date21-Feb-2002
PublisherAmerican Physical Society
CitationPhysical Review E 65(3): 036123.1-036123.5 (2002)
AbstractWe propose a model for growing networks based on a finite memory of the nodes. The model shows stylized features of real-world networks: power law distribution of degree, linear preferential attachment of new links and a negative correlation between the age of a node and its link attachment rate. Notably, the degree distribution is conserved even though only the most recently grown part of the network is considered. As the network grows, the clustering reaches an asymptotic value larger than for regular lattices of the same average connectivity and similar to the one observed in the networks of movie actors, coauthorship in science, and word synonyms. These high-clustering scale-free networks indicate that memory effects could be crucial for a correct description of the dynamics of growing networks.
Description5 pages, 4 figures.-- PACS number(s): 89.75.Hc, 87.23.Ge, 89.65.2s
Publisher version (URL)http://dx.doi.org/10.1103/PhysRevE.65.036123
URIhttp://hdl.handle.net/10261/18030
DOI10.1103/PhysRevE.65.036123
ISSN1539-3755
Appears in Collections:(IMEDEA) Artículos
(IFISC) Artículos
Files in This Item:
File Description SizeFormat 
hcsf.pdf79,9 kBAdobe PDFThumbnail
View/Open
Show full item record
Review this work
 

Related articles:


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.