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dc.date.accessioned2009-04-20T10:09:03Z
dc.date.available2009-04-20T10:09:03Z
dc.date.issued2007
dc.identifier.uriurn:nbn:de:hebis:34-2009042027044
dc.identifier.urihttp://hdl.handle.net/123456789/2009042027044
dc.format.extent5770237 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.subject.ddc004
dc.titleNetwork properties of folksonomieseng
dc.typePreprint
dcterms.abstractSocial resource sharing systems like YouTube and del.icio.us have acquired a large number of users within the last few years. They provide rich resources for data analysis, information retrieval, and knowledge discovery applications. A first step towards this end is to gain better insights into content and structure of these systems. In this paper, we will analyse the main network characteristics of two of these systems. We consider their underlying data structures â so-called folksonomies â as tri-partite hypergraphs, and adapt classical network measures like characteristic path length and clustering coefficient to them. Subsequently, we introduce a network of tag cooccurrence and investigate some of its statistical properties, focusing on correlations in node connectivity and pointing out features that reflect emergent semantics within the folksonomy. We show that simple statistical indicators unambiguously spot non-social behavior such as spam.eng
dcterms.accessRightsopen access
dcterms.creatorCattuto, Ciro
dcterms.creatorSchmitz, Christoph
dcterms.creatorBaldassarri, Andrea
dcterms.creatorServedio, Vito D. P.
dcterms.creatorLoreto, Vittorio
dcterms.creatorHotho, Andreas
dcterms.creatorGrahl, Miranda
dcterms.creatorStumme, Gerd
dc.description.everythingAuch erschienen in: AI Communications. Amsterdam : IOP Press, 2007, Vol. 20, 4, S. 245-262. ISSN 0921-7126ger
dc.subject.swdWissenserwerbger
dc.subject.swdWissensmanagementger


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