User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse




Conference Paper

Characterizing a social bookmarking and tagging network


Angelova,  Ralitsa
Databases and Information Systems, MPI for Informatics, Max Planck Society;

There are no locators available
Fulltext (public)
There are no public fulltexts available
Supplementary Material (public)
There is no public supplementary material available

Angelova, R., Lipczak, M., Milios, E., & Prałat, P. (2008). Characterizing a social bookmarking and tagging network. In Proceedings of the ECAI 2008 Workshop on Mining Social Data (MSoDa) (pp. 21-25). http://www.iospress.nl/: IOS.

Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-1B30-5
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.us 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 assigned 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 “similar” users. Here, similarity can reflect different aspects of the user’s 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 additional 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.