User-Generated Metadata in Social Software: An Analysis of Findability in Content Tagging and Recommender Systems
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Date
2007-03
Authors
Barnes, Michael
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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].
Keywords
Applied Information Management, Social software applications, Metadata, Information classification, Information discovery, Recommender systems, Content tagging, Information retrieval, AIM, Data