The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Can all tags be used for search?
Abstract
Collaborative tagging has become an increasingly popular means for sharing and organizing Web resources, leading to a huge amount of user generated metadata. These tags represent quite a few different aspects of the resources they describe and it is not obvious whether and how these tags or subsets of them can be used for search. This paper is the first to present an in-depth study of tagging behavior for very different kinds of resources and systems - Web pages (Del.icio.us), music (Last.fm), and images (Flickr) - and compares the results with anchor text characteristics. We analyze and classify sample tags from these systems, to get an insight into what kinds of tags are used for different resources, and provide statistics on tag distributions in all three tagging environments. Since even relevant tags may not add new information to the search procedure, we also check overlap of tags with content, with metadata assigned by experts and from other sources. We discuss the potential of different kinds of tags for improving search, comparing them with user queries posted to search engines as well as through a user survey. The results are promising and provide more insight into both the use of different kinds of tags for improving search and possible extensions of tagging systems to support the creation of potentially search-relevant tags.
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Citations
Cites
A Coefficient of Agreement for Nominal Scales
Cohen, J. (1960) · Educational and Psychological Measurement · doi:10.1177/001316446002000104 · Cited by 42,398
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Golder, S. A., & Huberman, B. A. (2006) · Journal of Information Science · doi:10.1177/0165551506062337 · Cited by 1,817
HT06, tagging paper, taxonomy, Flickr, academic article, to read
Marlow, C., Naaman, M., Boyd, D., & Davis, M. (2006) · Proceedings of the seventeenth conference on Hypertext and hypermedia · doi:10.1145/1149941.1149949 · Cited by 877
Information Retrieval in Folksonomies: Search and Ranking
Hotho, A., Jäschke, R., Schmitz, C., & Stumme, G. (2006) · Lecture Notes in Computer Science · doi:10.1007/11762256_31 · Cited by 845
Why we tag: motivations for annotation in mobile and online media
Ames, M., & Naaman, M. (2007) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240772 · Cited by 833
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The complex dynamics of collaborative tagging
Halpin, H., Robu, V., & Shepherd, H. (2007) · Proceedings of the 16th international conference on World Wide Web · doi:10.1145/1242572.1242602 · Cited by 603
Optimizing web search using social annotations
Bao, S., Xue, G., Wu, X., Yu, Y., Fei, B., & Su, Z. (2007) · Proceedings of the 16th international conference on World Wide Web · doi:10.1145/1242572.1242640 · Cited by 546
The Kappa Statistic: A Second Look
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Cited by
Latent dirichlet allocation for tag recommendation
Krestel, R., Fankhauser, P., & Nejdl, W. (2009) · Proceedings of the third ACM conference on Recommender systems · doi:10.1145/1639714.1639726 · Cited by 494
Self-citationPower Law Distributions in Information Retrieval
Petersen, C., Simonsen, J. G., & Lioma, C. (2016) · ACM Transactions on Information Systems · doi:10.1145/2816815 · Cited by 46
How annotation styles influence content and preferences
Cheng, J., & Cosley, D. (2013) · Proceedings of the 24th ACM Conference on Hypertext and Social Media · doi:10.1145/2481492.2481519 · Cited by 14
Metadata
- Authors
- Bischoff, K., Firan, C. S., Nejdl, W., & Paiu, R.
- Venue
- Proceedings of the 17th ACM conference on Information and knowledge management
- Publisher
- ACM
- Published
- 2008-10-26
- Pages
- 193-202
- OpenAlex
- W1978577143
- Cited by
- 290
- References
- 18
- FWCI
- 31.21
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Bischoff, K., Firan, C. S., Nejdl, W., & Paiu, R. (2008). Can all tags be used for search? Proceedings of the 17th ACM conference on Information and knowledge management. https://doi.org/10.1145/1458082.1458112
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.