1Network Properties of Folksonomies

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 discov-ery 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 net-work characteristics of two of these systems. We con-sider their underlying data structures – so-called folk-sonomies – as tri-partite hypergraphs, and adapt clas-sical 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 prop-erties, focusing on correlations in node connectivity and pointing out features that reflect emergent seman-tics within the folksonomy. We show that simple sta-tistical indicators unambiguously spot non-social be-havior such as spam. 1