Publication: Characterizing a social bookmarking and tagging network
All || By Area || By Year| Title | Characterizing a social bookmarking and tagging network | Authors/Editors* | R. Angelova, M. Lipczak, E. Milios, P. Pralat |
|---|---|
| Where published* | Proceedings of the 18th European Conference on Artificial Intelligence -- Workshop on Mining Social Data (MSoDa) |
| How published* | Proceedings |
| Year* | 2008 |
| Volume | |
| Number | |
| Pages | 21-25 |
| Publisher | |
| Keywords | |
| Link | http://www.math.ryerson.ca/~pralat/research.html |
| Abstract |
Social networks and collaborative tagging systems are rapidly gaining popularity as a primary means for storing and sharing data among friends, family, colleagues, or perfect strangers as long as they have common interests. del.icio.us5 is a social network where people store and share their personal bookmarks. Most importantly, users tag their bookmarks for ease of information dissemination and later look up. However, it is the friendship links, that make delicious a social network. They exist independently of the set of bookmarks that belong to the users and have no relation to the tags typically as- signed to the bookmarks. To study the interaction among users, the strength of the existing links and their hidden meaning, we introduce implicit links in the network. These links connect only highly âsim- ilarâ users. Here, similarity can reflect different aspects of the userâs profile that makes her similar to any other user, such as number of shared bookmarks, or similarity of their tags clouds. We investigate the question whether friends have common interests, we gain addi- tional insights on the strategies that users use to assign tags to their bookmarks, and we demonstrate that the graphs formed by implicit links have unique properties differing from binomial random graphs or random graphs with an expected power-law degree distribution. |
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