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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.