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Network properties of folksonomies
Abstract
Social 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 the
systems. We consider their underlying data structures – socalled folksonomies – 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 co-occurrence 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.
content and structure of these systems. In this paper, we will analyse the main network characteristics of two of the
systems. We consider their underlying data structures – socalled folksonomies – 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 co-occurrence 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.
Citation
@article{urn:nbn:de:hebis:34-2009042027037,
author={Schmitz, Christoph and Grahl, Miranda and Hotho, Andreas and Stumme, Gerd and Cattuto, Ciro and Baldassarri, Andrea and Loreto, Vittorio and Servedio, Vito D. P.},
title={Network properties of folksonomies},
year={2007}
}
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3000 Schmitz, Christoph
3010 Grahl, Miranda
3010 Hotho, Andreas
3010 Stumme, Gerd
3010 Cattuto, Ciro
3010 Baldassarri, Andrea
3010 Loreto, Vittorio
3010 Servedio, Vito D. P.
4000 Network properties of folksonomies / Schmitz, Christoph
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<resource xsi:schemaLocation="http://datacite.org/schema/kernel-2.2 http://schema.datacite.org/meta/kernel-2.2/metadata.xsd"> 2009-04-20T09:58:34Z 2009-04-20T09:58:34Z 2007 urn:nbn:de:hebis:34-2009042027037 http://hdl.handle.net/123456789/2009042027037 4128811 bytes application/pdf eng Urheberrechtlich geschützt https://rightsstatements.org/page/InC/1.0/ 004 Network properties of folksonomies Preprint Social 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 the systems. We consider their underlying data structures – socalled folksonomies – 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 co-occurrence 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. open access Schmitz, Christoph Grahl, Miranda Hotho, Andreas Stumme, Gerd Cattuto, Ciro Baldassarri, Andrea Loreto, Vittorio Servedio, Vito D. P. Auch erschienen in: Proceedings. WWW2007 Workshop "Tagging and Metadata for Social Information Organization". Banff, 2007. Wissenserwerb Wissensmanagement </resource>
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