Unsupervised learning by probabilistic latent semantic analysis
Machine Learning
Usage patterns of collaborative tagging systems
Journal of Information Science
Discovering leaders from community actions
Proceedings of the 17th ACM conference on Information and knowledge management
Why do people tag?: motivations for photo tagging
Communications of the ACM
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We study in a quantitative way whether the most popular tags in a collaborative tagging system are distinctive features when looking at the underlying content. For any set of annotations being helpful in searching, this property must necessarily hold to a strong degree. Our initial experiments show that the most frequent tags in CiteULike are distinctive features, despite the process of annotating documents is not centrally coordinated nor correction mechanisms like in a Wiki-system are used.