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Social Networks and Interest Similarity: The Case of CiteULike

Lee, Danielle and Brusilovsky, Peter (2010) Social Networks and Interest Similarity: The Case of CiteULike. In: 21st ACM Conference on Hypertext and Hypermedia (HT '10), June 14 ~ 16, 2010, Toronto Canada.


In collaborative filtering recommender systems, there is little room for users to get involved in the choice of their peer group. It leaves users defenseless against various spamming or ''shilling'' attacks. Other social Web-based systems, however, allow users to self-select peers and build a social network. We argue that users' self-defined social networks could be valuable to increase the quality of recommendation in CF systems. To prove the feasibility of this idea we examined how similar are interests of users connected by self-defined relationships in a collaborative tagging systems Citeulike. Interest similarity was measured by similarity of items and meta-data they share and tags they use. Our study shows that users connected by social networks exhibit significantly higher similarity on all explored levels (items, meta-data, and tags) than non-connected users. This similarity is the highest for directly connected users and decreases with the increase of distance between users. Among other interesting properties of information sharing is the finding that between-user similarity in social connections on the level of metadata and tags is much larger than similarity on the level of items. Overall, our findings support the feasibility of social network based recommender systems and offer some good hints to the prospective authors of these systems.


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Item Type: Conference or Workshop Item (Paper)
Status: Published
CreatorsEmailPitt UsernameORCID
Lee, Daniellehyl12@pitt.eduHYL12
Brusilovsky, Peterpeterb@pitt.eduPETERB0000-0002-1902-1464
Date: June 2010
Date Type: Publication
Publisher: ACM
Place of Publication: New York
Page Range: pp. 151-156
Event Title: 21st ACM Conference on Hypertext and Hypermedia (HT '10)
Event Dates: June 14 ~ 16, 2010
Event Type: Conference
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Official URL:
Other ID: DOI: 10.1145/1810617.1810643, ISBN: 978-1-4503-0041-4
Additional Information: Access to the full text is subject to the publisher's access restrictions.
Date Deposited: 06 Jul 2011 19:19
Last Modified: 15 Nov 2016 13:35


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