Enhancing information scent: Identifying and recommending quality tags

Shaoke Zhang, Umer Farooq, John M. Carroll

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationGROUP'09 - Proceedings of the 2009 ACM SIGCHI International Conference on Supporting Group Work
Pages1-10
Number of pages10
DOIs
StatePublished - Dec 1 2009
Event2009 ACM SIGCHI International Conference on Supporting Group Work, GROUP'09 - Sanibel Island, FL, United States
Duration: May 10 2009May 13 2009

Publication series

NameGROUP'09 - Proceedings of the 2009 ACM SIGCHI International Conference on Supporting Group Work

Other

Other2009 ACM SIGCHI International Conference on Supporting Group Work, GROUP'09
CountryUnited States
CitySanibel Island, FL
Period5/10/095/13/09

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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