Enhancing Information Scent: Identifying and Recommending Quality Tags

Simple item page
dc.contributor.authorZhang, Shaoke
dc.contributor.authorFarooq, Umer
dc.contributor.authorCarroll, John M.
dc.date.accessioned2023-06-08T11:44:30Z
dc.date.available2023-06-08T11:44:30Z
dc.date.issued2009
dc.description.abstractWe 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."en
dc.identifier.doi10.1145/1531674.1531676
dc.identifier.urihttps://dl.eusset.eu/handle/20.500.12015/4858
dc.language.isoen
dc.publisherAssociation for Computing Machinery
dc.relation.ispartofProceedings of the 2009 ACM International Conference on Supporting Group Work
dc.subjectsocial bookmarking
dc.subjectsense-making
dc.subjectquality tags
dc.titleEnhancing Information Scent: Identifying and Recommending Quality Tagsen
gi.citation.publisherPlaceNew York, NY, USA
gi.citation.startPage1–10
gi.conference.locationSanibel Island, Florida, USA

Files

Collections

GROUP 2009