Clustering Algorithms
Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Analysis of online video search and sharing
Proceedings of the eighteenth conference on Hypertext and hypermedia
I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Youtube traffic characterization: a view from the edge
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Characterizing social cascades in flickr
Proceedings of the first workshop on Online social networks
Wikipedia workload analysis for decentralized hosting
Computer Networks: The International Journal of Computer and Telecommunications Networking
Computer Networks: The International Journal of Computer and Telecommunications Networking
Ethics and information systems -- Guest editors' introduction
Information Systems Frontiers
Identifying valuable customers on social networking sites for profit maximization
Expert Systems with Applications: An International Journal
Self-disclosure at social networking sites: An exploration through relational capitals
Information Systems Frontiers
Web 2.0 Recommendation service by multi-collaborative filtering trust network algorithm
Information Systems Frontiers
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Online social networks have attracted millions of users, who have integrated social network web sites into their daily life. Users participate to the changes and to the evolution of these sites because they are producers and reviewers of contents that help them to maintain the existing social relationships, make new friends, collaborate and enrich experiences. This paper presents a study of the characteristics of the users of MySpace web site, with the objective of studying relationships and interactions among users and deriving hints about their behavior. The analysis relies on data collected by monitoring the web site for 12 weeks. Typical user behaviors have been derived and classes of users characterized by different levels of participation to the social network have been identified. In particular, the analysis reveals that most of the users actively participate to the social network and specify many personal details. Social networks web sites allow access to such details; the sharing of information about users and their relationships can lead to non-ethic online activities, which threat the privacy and the security of users themselves.