Dynamics of Online Tagging

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Brief and Incomplete Description

A number of researchers have observed, some casually, some more rigorously, that the distribution of tags applied to particular URLs in online social tagging systems such as del.icio.us and flickr follow a power law distribution. The central question involved is when and how a coherent classification system might emerge from the distributed tagging process. Is there a critical point beyond which a classification system is relatively stable? What are the dynamics of the system prior to this point? This process is of interest to the computer science community given that there remains a lack of consensus about whether tagging or classifications systems more efficiently organize information. Of interest to the social sciences is the issue of how actors following particular rules, which may be relatively idiosyncratic, or conventions for tagging cites interact through the feedback about tags and the distribution of tags to produce relatively coordinated emergent classification systems. Classification systems, once in place, naturally shape and constrain future behavior as they guide cognition. Additionally important is the issue of the role of language usage in tagging systems. Cattuto, Loreto & Pietronero (2006) note that “the emergence of a folksonomy exhibits dynamical aspects also observed in human languages, such as the crystallization of naming conventions, competition between terms, takeovers by neologisms, and more” (p. 2).

This project intends to use data collected from these online tagging sites to analyze the dynamics of these systems.

Proposed analyses:

1. Network evolution and dynamics of a two mode URL/tag network on a substantive area from del.icio.us over the course of the time the URLs became tagged on del.icio.us. 2. Analysis of changes in the distribution of tags over the period a URL has been tagged. a.Comparison over substantive areas? 3. Short-period (e.g. one week) evolution of the distribution of tags for news stories on del.icio.us.

Participants

Harry, Hana

Note!!! We are really interested in having anyone else join and especially people who are more adept at nonlinear dynamic analyses or we are at least interested in getting some advice about the type of analyses to pursue. Also, there is the possibility to apply information theoretical perspectives to the analysis of tags, if anyone is interested in that.