Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Usage patterns of collaborative tagging systems
Journal of Information Science
tagging, communities, vocabulary, evolution
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Can social bookmarking improve web search?
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Can all tags be used for search?
Proceedings of the 17th ACM conference on Information and knowledge management
Modeling and Data Mining in Blogosphere
Modeling and Data Mining in Blogosphere
A comparative study of Flickr tags and index terms in a general image collection
Journal of the American Society for Information Science and Technology
Member activities and quality of tags in a collection of historical photographs in Flickr
Journal of the American Society for Information Science and Technology
Journal of Information Science
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
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This article identifies patterns and structures in the social tagging of scholarly articles in CiteULike. Using a dataset of 4,215 tags attributed to 1,600 scholarly articles from 15 library and information science journals, a network was built to understand users' information organization behavior. Social network analysis and the frequent-pattern tree method were used to discover the implicit patterns and structures embedded in social tags as well as in their use, based on 26 proposed tag categories. The pattern and structure of this network of social tags is characterized by power-law distribution, centrality, co-used tag categories, role sharing among tag categories, and similar roles of tag categories in associating distinct tag categories. Furthermore, researchers generated 21 path-based decision-making sub-trees providing valuable insights into user tagging behavior for information organization professionals. The limitations of this study and future research directions are discussed.