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

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dc.contributor.authorBarnes, Michael
dc.date.accessioned2008-11-03T20:31:18Z
dc.date.available2008-11-03T20:31:18Z
dc.date.issued2007-03
dc.description131 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].en
dc.description.abstractThis 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.en
dc.identifier.urihttps://hdl.handle.net/1794/7670
dc.relation.ispartofseriesAIM Capstone 2007;Michael Barnes
dc.subjectApplied Information Managementen
dc.subjectSocial software applicationsen
dc.subjectMetadataen
dc.subjectInformation classificationen
dc.subjectInformation discoveryen
dc.subjectRecommender systemsen
dc.subjectContent taggingen
dc.subjectInformation retrievalen
dc.subjectAIMen
dc.subjectDataen
dc.titleUser-Generated Metadata in Social Software: An Analysis of Findability in Content Tagging and Recommender Systemsen
dc.typeOtheren

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