Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
The complex dynamics of collaborative tagging
Proceedings of the 16th international conference on World Wide Web
Analysis of topological characteristics of huge online social networking services
Proceedings of the 16th international conference on World Wide Web
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Spatio-temporal small worlds for decentralized information retrieval in social networking
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
A Survey on Database Performance in Virtualized Cloud Environments
International Journal of Data Warehousing and Mining
Estimation algorithm for counting periodic orbits in complex social networks
Information Systems Frontiers
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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.us3 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 del.icio.us 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. The authors investigate the question whether friends have common interests, they gain additional insights on the strategies that users use to assign tags to their bookmarks, and they 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.