Journal article
Network Properties of Folksonomies



Publication Details
Authors:
Stumme, G.; Hotho, A.; Schmitz, C.
Editor:
Hoche Susanne, Nürnberger Andreas, Flach Jürgen
Publisher:
IOS Press
Publication year:
2007
Journal:
AI Communications
Pages range:
245-262
Volume number:
20
ISSN:
0921-7126

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 these systems. We consider their underlying data structures - so-called 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.


Keywords
emergent, fca, folksonomies, folksonomy, itegpub, l3s, network, semantics, seminar2009, tagorapub

Last updated on 2019-25-07 at 15:42