User-Generated Metadata in Social Software: An Analysis of Findability in Content Tagging and Recommender Systems

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Title: User-Generated Metadata in Social Software: An Analysis of Findability in Content Tagging and Recommender Systems
Author: Barnes, Michael
Abstract: This study describes how user-generated metadata may be leveraged to enhance findability in web-based social software applications (Morville, 2005). Two interaction design systems, content tagging (Golder & Huberman, 2005) and recommender systems (Resnick & Varian, 1997), are examined to identify strengths and weaknesses along three findability factors: information classification, information retrieval and information discovery. Greater overall findability strength may be found in content tagging systems than in recommender systems.
Description: 131 p. This paper was completed as part of the final research component in the University of Oregon Applied Information Management Master's Degree Program [see htpp://aim.uoregon.edu].
URI: http://hdl.handle.net/1794/7670
Date: 2007-03


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