Information-Theoretic Models of Tagging

Author Harry Halpin

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Harry Halpin

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Harry Halpin. Information-Theoretic Models of Tagging. In Social Web Communities. Dagstuhl Seminar Proceedings, Volume 8391, pp. 1-2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)


In earlier work, we showed using Kulback-Leibler (KL) divergence that tags form a power law distribution very quickly. Yet there is one major observed deviation from the ideal power law distribution for the top 25 tags, a large "bump" in increased frequency for the top 7-10 tags. We originally hypothesized that the "bump" in the data could be caused by a preferential attachment mechanism. However, an experiment that tested both feedback and no-feedback conditions over tagging (200+ subjects) shows that the power law distribution arises regardless of any feedback effect. We hypothesize that an information-theoretic analysis of tags lead to a power law without feedback.
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