Enhancing information scent: identifying and recommending quality tags

We describe a scenario of tag use and an empirical study of tags as socio-cognitive artifacts providing information scent. We articulated a three-step use scenario of tags, and used it to conceptualize tag "quality" as determined by use. We designed and conducted a user study to explore what attributes of tags and taggers predict the user-rated "quality" of tags. We found that frequency best predicted tag quality, while information entropy provided further refinement. We found that people rated our identified quality tags as higher in quality than general tags. But these identified quality tags were not perceived as better than self-generated tags. We derived a regression model for tag quality and discussed implications for social computing.

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