document: The complex dynamics of collaborative tagging The debate within the Web community over the optimal means by which to organize information often pits formalized classifications against distributed collaborative tagging systems . A number of questions remain unanswered , however , regarding the nature of collaborative tagging systems including whether coherent categorization schemes can emerge from unsupervised tagging by users . This paper uses data from the social bookmarking site delicio . us to examine the dynamics of collaborative tagging systems . In particular , we examine whether the distribution of the frequency of use of tags for `` popular '' sites with a long history ( many tags and many users ) can be described by a power law distribution , often characteristic of what are considered complex systems . We produce a generative model of collaborative tagging in order to understand the basic dynamics behind tagging , including how a power law distribution of tags could arise . We empirically examine the tagging history of sites in order to determine how this distribution arises over time and to determine the patterns prior to a stable distribution . Lastly , by focusing on the high-frequency tags of a site where the distribution of tags is a stabilized power law , we show how tag co-occurrence networks for a sample domain of tags can be used to analyze the meaning of particular tags given their relationship to other tags .
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