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Information-Theoretic Models of Tagging Halpin, Harry Tagging information theory feedback 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Harry Halpin 2008 Is Part Of Dagstuhl Seminar Proceedings, Volume 8391, Social Web Communities (2008) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.08391.8 urn:nbn:de:0030-drops-17876 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08391.8 eng https://creativecommons.org/licenses/by/4.0/legalcode