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How to Measure the Information Similarity in Unilateral Relations: The Case Study of Delicious

Lee, Danielle (2010) How to Measure the Information Similarity in Unilateral Relations: The Case Study of Delicious. In: International Workshop on Modeling Social Media 2010 (MSM '10), the 21st ACM Conference on Hypertext and Hypermedia, June 14 ~ 16, 2010, Toronto, Ontario, Canada.

Abstract

In this paper, I describe a better way to compute the information similarity between two users who are unilaterally connected. Unilateral relations are unidirectional connections and gain attention with the success of social tagging and microblogging systems. The relations are convenient and less bounded since people can make the connection without mutual agreement once they perceive that other users’ information is worth. Using a social bookmarking data set, Delicious, I found that the traditional item unit-based similarity measures are not enough to show the common interests between a pair of unilaterally connected users. The similarity measure on the higher level such as metadata (root address of each URL) and macro-level tags (tags regardless of the annotated information item) showed better results. The significantly better results in metadata and macro-tag level similarity were also shown in the indirect relations, as well. I interpreted this result to mean that semantic information such as metadata and tags represent users’ cognitive understanding of corresponding information. Therefore, in social tagging systems, it is better to match users not based on item-level similarity but based on the similarity on a higher level which embeds more semantic meanings.


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Details

Item Type: Conference or Workshop Item (Paper)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Lee, Daniellehyl12@pitt.eduHYL12
Date: June 2010
Publisher: ACM
Place of Publication: New York
Event Title: International Workshop on Modeling Social Media 2010 (MSM '10), the 21st ACM Conference on Hypertext and Hypermedia
Event Dates: June 14 ~ 16, 2010
Event Type: Workshop
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Official URL: http://doi.acm.org/10.1145/1835980.1835981
Related URLs:
Other ID: DOI: 10.1145/1835980.1835981
Additional Information: Access to the full text is subject to the publisher's access restrictions.
Date Deposited: 06 Jul 2011 19:14
Last Modified: 15 Nov 2016 13:35
URI: http://d-scholarship.pitt.edu/id/eprint/5969

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