Usage patterns of collaborative tagging systems
Journal of Information Science
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Reasonable tag-based collaborative filtering for social tagging systems
Proceedings of the 2nd ACM workshop on Information credibility on the web
Collaborative Filtering Recommender Systems Using Tag Information
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Proceedings of the Second ACM International Conference on Web Search and Data Mining
EnTag: enhancing social tagging for discovery
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
No bull, no spin: a comparison of tags with other forms of user metadata
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
A statistical comparison of tag and query logs
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
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If researchers use tags in retrieval applications they might assume, implicitly, that tags represent novel information, e.g., when they attribute performance improvement in their retrieval algorithm(s) to the use of tags. In this work, we investigate whether this assumption is true. We focus on the use of tags in domain-specific websites because such websites are more likely to have a coherent, discernible website structure and because the users that are searching for and tagging pages in such a site may have specific information needs (as opposed to the broad range of information needs that users have when browsing/searching the Internet at large). For this study, we assume that the application of the same tag to multiple pages provides an indication that those pages are related. To determine whether this indication of relatedness is contributing new information, we first measure whether pages with common tag(s) could have been deemed as related based on site structure as measured by shortest navigational distance between pages. Second, we measure whether or not tags could have been determined algorithmically based on standard tf-idf scores of terms on the page. Based on our analysis of two different sites, we found that tags contribute novel information that is not discernible from site structure or site/page content.