Core-periphery clustering and collaboration networks

Pierluigi Crescenzi, Pierre Fraigniaud, Zvi Lotker, Paolo Penna

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper we analyse the core-periphery clustering properties of collaboration networks, where the core of a network is formed by the nodes with highest degree. In particular, we first observe that, even for random graph models aiming at matching the degree-distribution and/or the clustering coefficient of real networks, these models produce synthetic graphs which have a spatial distribution of the triangles with respect to the core and to the periphery which does not match the spatial distribution of the triangles in the real networks. We therefore propose a new model, called CPCL, whose aim is to distribute the triangles in a way fitting with their real core-periphery distribution, and thus producing graphs matching the core-periphery clustering of real networks.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
EditorsRavi Kumar, James Caverlee, Hanghang Tong
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages525-528
Number of pages4
ISBN (Electronic)9781509028467
DOIs
StatePublished - 21 Nov 2016
Externally publishedYes
Event2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States
Duration: 18 Aug 201621 Aug 2016

Publication series

NameProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

Conference

Conference2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
Country/TerritoryUnited States
CitySan Francisco
Period18/08/1621/08/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Funding

The first author received additional support from MIUR, under PRIN 2012C4E3KT project AMANDA. The second author received additional support from ANR project DISPLEXITY and Inria project GANG. The third author is supported by FSMP, and is hosted at IRIF. Part of this work was done while the fourth author was visiting IRIF supported by ANR project DISPLEXITY

FundersFunder number
Agence Nationale de la Recherche
Ministero dell’Istruzione, dell’Università e della RicercaPRIN 2012C4E3KT
Fondation Sciences Mathématiques de Paris

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