Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/5831
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dc.contributor.authorPapadopoulos, Fragkiskos-
dc.contributor.authorKitsak, Maksim-
dc.contributor.authorSerrano, Angeles M.-
dc.contributor.authorBoguna, Marian-
dc.contributor.authorKrioukov, Dmitri-
dc.date.accessioned2012-10-03T07:24:00Z-
dc.date.accessioned2013-05-17T10:30:49Z-
dc.date.accessioned2015-12-09T11:29:36Z-
dc.date.available2012-10-03T07:24:00Z-
dc.date.available2013-05-17T10:30:49Z-
dc.date.available2015-12-09T11:29:36Z-
dc.date.issued2012-09-12-
dc.identifier.citationNature, 2012, vol. 489, no. 7417, pp. 537–540en_US
dc.identifier.issn1476-4687-
dc.description.abstractThe principle that popularity is attractive underlies preferential attachment, which is a common explanation for the emergence of scaling in growing networks. If new connections are made preferentially to more popular nodes, then the resulting distribution of the number of connections possessed by nodes follows power laws as observed in many real networks. Preferential attachment has been directly validated for some real networks (including the Internet), and can be a consequence of different underlying processes based on node fitness, ranking, optimization, random walks or duplication. Here we show that popularity is just one dimension of attractiveness; another dimension is similarity. We develop a framework in which new connections optimize certain trade-offs between popularity and similarity, instead of simply preferring popular nodes. The framework has a geometric interpretation in which popularity preference emerges from local optimization. As opposed to preferential attachment, our optimization framework accurately describes the large-scale evolution of technological (the Internet), social (trust relationships between people) and biological (Escherichia coli metabolic) networks, predicting the probability of new links with high precision. The framework that we have developed can thus be used for predicting new links in evolving networks, and provides a different perspective on preferential attachment as an emergent phenomenon.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.publisherMacmillan Publishers-
dc.relation.ispartofNatureen_US
dc.rights@ 2012 Natureen_US
dc.subjectApplied physicsen_US
dc.subjectEngineeringen_US
dc.subjectPhysicsen_US
dc.titlePopularity Versus Similarity in Growing Networksen_US
dc.typeArticleen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationUniversity of California, San Diegoen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.reviewPeer reviewed-
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1038/nature11459en_US
dc.identifier.pmid489-
dc.identifier.scopus2-s2.0-84866920330-
dc.dept.handle123456789/134-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84866920330-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.relation.issue7417en_US
dc.relation.volume489en_US
cut.common.academicyear2012-2013en_US
dc.identifier.spage537en_US
dc.identifier.epage540en_US
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.openairetypearticle-
item.cerifentitytypePublications-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-4072-5781-
crisitem.author.parentorgFaculty of Engineering and Technology-
crisitem.journal.journalissn1476-4687-
crisitem.journal.publisherSpringer Nature-
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