The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Can social bookmarking improve web search?
Abstract
Social bookmarking is a recent phenomenon which has the potential to give us a great deal of data about pages on the web. One major question is whether that data can be used to augment systems like web search. To answer this question, over the past year we have gathered what we believe to be the largest dataset from a social bookmarking site yet analyzed by academic researchers. Our dataset represents about forty million bookmarks from the social bookmarking site del.icio.us. We contribute a characterization of posts to del.icio. us: how many bookmarks exist (about 115 million), how fast is it growing, and how active are the URLs being posted about (quite active). We also contribute a characterization of tags used by bookmarkers. We found that certain tags tend to gravitate towards certain domains, and vice versa. We also found that tags occur in over 50 percent of the pages that they annotate, and in only 20 percent of cases do they not occur in the page text, backlink page text, or forward link page text of the pages they annotate. We conclude that social bookmarking can provide search data not currently provided by other sources, though it may currently lack the size and distribution of tags necessary to make a significant impact
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Cites
Usage patterns of collaborative tagging systems
Golder, S. A., & Huberman, B. A. (2006) · Journal of Information Science · doi:10.1177/0165551506062337 · Cited by 1,817
The vocabulary problem in human-system communication
Furnas, G. W., Landauer, T. K., Gomez, L. M., & Dumais, S. T. (1987) · Communications of the ACM · doi:10.1145/32206.32212 · Cited by 1,504
N-gram-based text categorization
Cavnar, W. B., & Trenkle, J. M. (1994) · Cited by 1,497
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
Pass, G., Chowdhury, A., & Torgeson, C. (2006) · Proceedings of the 1st international conference on Scalable information systems - InfoScale '06 · doi:10.1145/1146847.1146848 · Cited by 666
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
tagging, communities, vocabulary, evolution
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Effective site finding using link anchor information
Craswell, N., Hawking, D., & Robertson, S. (2001) · Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval · doi:10.1145/383952.383999 · Cited by 269
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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
Heymann, P., Ramage, D., & Garcia-Molina, H. (2008) · Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval · doi:10.1145/1390334.1390425 · Cited by 311
Self-citationCan all tags be used for search?
Bischoff, K., Firan, C. S., Nejdl, W., & Paiu, R. (2008) · Proceedings of the 17th ACM conference on Information and knowledge management · doi:10.1145/1458082.1458112 · Cited by 290
Evaluating similarity measures for emergent semantics of social tagging
Markines, B., Cattuto, C., Menczer, F., Benz, D., Hotho, A., & Stumme, G. (2009) · Proceedings of the 18th international conference on World wide web · doi:10.1145/1526709.1526796 · Cited by 287
Personalization and privacy: a survey of privacy risks and remedies in personalization-based systems
Toch, E., Wang, Y., & Cranor, L. F. (2012) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-011-9110-z · Cited by 226
Metadata
- Authors
- Heymann, P., Koutrika, G., & Garcia-Molina, H.
- Venue
- Proceedings of the international conference on Web search and web data mining - WSDM '08
- Publisher
- ACM Press
- Published
- 2008
- Pages
- 195
- OpenAlex
- W2124916819
- Cited by
- 434
- References
- 13
- Type
- conference abstract
- Language
- en
- Open access
- closed
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- Heymann, P., Koutrika, G., & Garcia-Molina, H. (2008). Can social bookmarking improve web search? Proceedings of the international conference on Web search and web data mining - WSDM '08. https://doi.org/10.1145/1341531.1341558
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