Repository logo
 
Publication

A data reduction approach using hypergraphs to visualize communities and brokers in social networks

dc.contributor.authorCavique, Luís
dc.contributor.authorMarques, Nuno C.
dc.contributor.authorGonçalves, António
dc.date.accessioned2018-11-05T14:55:44Z
dc.date.available2018-11-05T14:55:44Z
dc.date.issued2018
dc.description.abstractThe comprehension of social network phenomena is closely related to data visualization. However, even with only hundreds of nodes, the visualization of dense networks is usually difficult. The strategy adopted in this work is data reduction using communities. Community detection in social network analysis is a very important issue and in particular detection of community overlapping. In this approach, the information extracted from social networks transcends cohesive groups, enabling the discovery of brokers that interact among communities. In order to find admissible solutions in hard problems, relaxed approaches are used. Quasi-cliques are generated, and partition is found using a partial set covering heuristic. The proposed method allows the identification of communities and actors that link two or more groups. In the visualization process, the user can choose different dimension reduction approaches for the condensed graph. For each condensed structure a hypergraph can be drawn, identifying communities and brokers.pt_PT
dc.description.sponsorshipThe first author would like to thank the FCT UID/Multi/04046/2013 for its support.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/s13278-018-0538-6pt_PT
dc.identifier.issn1869-5450 (Print)
dc.identifier.issn1869-5469 (Online)
dc.identifier.urihttp://hdl.handle.net/10400.2/7637
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectGraph miningpt_PT
dc.subjectData reductionpt_PT
dc.subjectCommunity detectionpt_PT
dc.subjectBrokeragept_PT
dc.subjectHypergraphspt_PT
dc.titleA data reduction approach using hypergraphs to visualize communities and brokers in social networkspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FMulti%2F04046%2F2013/PT
oaire.citation.issue1pt_PT
oaire.citation.titleSocial Network Analysis and Miningpt_PT
oaire.citation.volume8pt_PT
oaire.fundingStream5876
person.familyNameCavique
person.givenNameLuís
person.identifier.ciencia-id911E-84AC-3956
person.identifier.orcid0000-0002-5590-1493
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication40906a16-46a2-42f1-b26d-7db7012294ee
relation.isAuthorOfPublication.latestForDiscovery40906a16-46a2-42f1-b26d-7db7012294ee
relation.isProjectOfPublicationab8b249f-48e9-42c8-8786-c1976e895516
relation.isProjectOfPublication.latestForDiscoveryab8b249f-48e9-42c8-8786-c1976e895516

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
paper SNAM sep 2018.pdf
Size:
909.11 KB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.97 KB
Format:
Item-specific license agreed upon to submission
Description: