Usage patterns of collaborative tagging systems
Journal of Information Science
Combating spam in tagging systems
AIRWeb '07 Proceedings of the 3rd international workshop on Adversarial information retrieval on the web
MultiTube--Where Web 2.0 and Multimedia Could Meet
IEEE MultiMedia
VideoSense: a contextual video advertising system
Proceedings of the 15th international conference on Multimedia
Computing block importance for searching on web sites
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Finding high-quality content in social media
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Proceedings of the 17th international conference on World Wide Web
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Tag-based social interest discovery
Proceedings of the 17th international conference on World Wide Web
Real-time automatic tag recommendation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Efficient top-k querying over social-tagging networks
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Can all tags be used for search?
Proceedings of the 17th ACM conference on Information and knowledge management
Social tags: meaning and suggestions
Proceedings of the 17th ACM conference on Information and knowledge management
Proceedings of the 18th Brazilian symposium on Multimedia and the web
Selecting keywords to represent web pages using Wikipedia information
Proceedings of the 18th Brazilian symposium on Multimedia and the web
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Despite the large amount of multimedia content in Web 2.0 applications, most of its services in Information Retrieval (IR) use only attributes associated with textual content (eg, labels or tags). However, because they are typically generated by users, such attributes do not offer guarantees of quality for IR services. Here, we investigate evidence of quality of textual attributes in popular Web 2.0 applications related to three aspects: utilization; discriminative and descriptive power. We have performed a characterization of the use of four textual attributes (title, description, tags and comments) in the following systems: Youtube, YahooVideo, LastFM and CiteULike. Some of our results, which may be considered in the design of IR services in Web 2.0, are: (1) collaborative textual attributes, although not significantly exploited in some applications, contain the largest amount of information when present, (2) there is a significant diversity of information between the textual attributes, and (3) the title and tags of the objects seem to be the most promising attributes for IR services, whereas the former is almost always present and has a high power specification, and second, when used, has a high discriminative and descriptive power.