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Article: Weighted assortative and disassortative networks model

TitleWeighted assortative and disassortative networks model
Authors
KeywordsAssortative and disassortative networks
Clustering
Evolving weighted network
Mean field approximation
Weighted assortativity coefficient
Issue Date2007
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/physa
Citation
Physica A: Statistical Mechanics And Its Applications, 2007, v. 378 n. 2, p. 591-602 How to Cite?
AbstractReal-world networks process structured connections since they have non-trivial vertex degree correlation and clustering. Here we propose a toy model of structure formation in real-world weighted network. In our model, a network evolves by topological growth as well as by weight change. In addition, we introduce the weighted assortativity coefficient, which generalizes the assortativity coefficient of a topological network, to measure the tendency of having a high-weighted link between two vertices of similar degrees. Network generated by our model exhibits scale-free behavior with a tunable exponent. Besides, a few non-trivial features found in real-world networks are reproduced by varying the parameter ruling the speed of weight evolution. Most importantly, by studying the weighted assortativity coefficient, we found that both topologically assortative and disassortative networks generated by our model are in fact weighted assortative. © 2007 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/80460
ISSN
2015 Impact Factor: 1.785
2015 SCImago Journal Rankings: 0.738
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLeung, CCen_HK
dc.contributor.authorChau, HFen_HK
dc.date.accessioned2010-09-06T08:06:42Z-
dc.date.available2010-09-06T08:06:42Z-
dc.date.issued2007en_HK
dc.identifier.citationPhysica A: Statistical Mechanics And Its Applications, 2007, v. 378 n. 2, p. 591-602en_HK
dc.identifier.issn0378-4371en_HK
dc.identifier.urihttp://hdl.handle.net/10722/80460-
dc.description.abstractReal-world networks process structured connections since they have non-trivial vertex degree correlation and clustering. Here we propose a toy model of structure formation in real-world weighted network. In our model, a network evolves by topological growth as well as by weight change. In addition, we introduce the weighted assortativity coefficient, which generalizes the assortativity coefficient of a topological network, to measure the tendency of having a high-weighted link between two vertices of similar degrees. Network generated by our model exhibits scale-free behavior with a tunable exponent. Besides, a few non-trivial features found in real-world networks are reproduced by varying the parameter ruling the speed of weight evolution. Most importantly, by studying the weighted assortativity coefficient, we found that both topologically assortative and disassortative networks generated by our model are in fact weighted assortative. © 2007 Elsevier B.V. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/physaen_HK
dc.relation.ispartofPhysica A: Statistical Mechanics and its Applicationsen_HK
dc.rightsPhysica A: Statistical Mechanics and its Applications. Copyright © Elsevier BV.en_HK
dc.subjectAssortative and disassortative networksen_HK
dc.subjectClusteringen_HK
dc.subjectEvolving weighted networken_HK
dc.subjectMean field approximationen_HK
dc.subjectWeighted assortativity coefficienten_HK
dc.titleWeighted assortative and disassortative networks modelen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0378-4371&volume=378&spage=591&epage=602&date=2007&atitle=Weighted+assortative+and+disassortative+networks+modelen_HK
dc.identifier.emailChau, HF: hfchau@hku.hken_HK
dc.identifier.authorityChau, HF=rp00669en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.physa.2006.12.022en_HK
dc.identifier.scopuseid_2-s2.0-33847657629en_HK
dc.identifier.hkuros126278en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33847657629&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume378en_HK
dc.identifier.issue2en_HK
dc.identifier.spage591en_HK
dc.identifier.epage602en_HK
dc.identifier.eissn1873-2119-
dc.identifier.isiWOS:000245531100042-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridLeung, CC=36725507200en_HK
dc.identifier.scopusauthoridChau, HF=7005742276en_HK

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