Towards Mining Semantic Maturity in Social Bookmarking Systems

The existence of emergent semantics within social metadata (such as tags in bookmarking systems) has been proven by a large number of successful approaches making the implicit semantic structures explicit. However, much less attention has been given to the factors which influence the “maturing” process of these structures over time. A natural hypothesis is that tags become semantically more and more mature whenever many users use them in the same contexts. This would allow to describe a tag by a specific and informative “semantic fingerprint” in the context of tagged resoures. However, the question of assessing the quality of such fingerprints has been seldomly addressed. In this paper, we provide a systematic approach of mining semantic maturity profiles within folksonomy-based tag properties. Our ultimate goal is to provide a characterization of “mature tags”. Additionally, we consider semantic information about the tags as a gold-standard source for the characterization of the collected results. Our initial results suggest that a suitable composition of tag properties allows the identification of more mature tag subsets. The presented work has implications for a number of problems related to social tagging systems, including tag ranking, tag recommendation, and the capturing of light-weight ontologies from tagging data.