Group items tagged

The recent announcement by Microsoft of a bid to acquire Yahoo! in a hostile takeover provides stark evidence of the continuing complexity of the intersection of computing and media businesses battling for dominance in the global market. Just as in the case of Time-Warner and AOL (Klein, 2003), the proposed Microsoft-Yahoo! deal is about convergence. The big difference, however, is the new context of threats and opportunities which have led to Redmond's latest effort to deploy its legendary financial muscle in pursuit of corporate goals of market domination. This difference emerges from changing conditions of networked media-computing which are in part associated with the rise of Web 2.0 and which provide an essential clue to understanding why Web 2.0 occupies such an important position in contemporary thinking about the Internet. As I will explain in this paper, Web 2.0 can itself be understood fully only by locating its emergence and significance within the broad movement of convergence of old and new media forms.

"The debate within the Web community over the optimal means by which to organize information often pits formalized classications 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 del.icio.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."

The paper shows that the tags users choose are not chaotic, but rather quickly converge to a common descriptive set of tags that is almost unchanging over time. Perhaps once the tags have stabilized, coherent URI-based identification schemes could emerge?

Nice paper, thanks. Categories / tags / subjects / topics / issues ... that's what I'm working with right now. p.s. sure would be nice if the email notification included the source URL. I'm far more likely to download the PDF when I see something like www2007.org/paper635.pdf