Abstract
Collaborative web 2.0 applications, such as blogs, collaborative bookmarking, file sharing etc., have increased significantly in popularity. In these user-centric applications users are not only consumers, but also contributors. By contributing content to the system, users become part of the network and relationships between users and content can be derived. Social network metrics can be used to identify key users, however, evaluating network metrics for a large scale network can be expensive. For this reason this paper explores the utility of localised network metrics. Experimental results and analysis are presented on a large collaborative IBM bookmarking network called Dogear to investigate the ability to identify central users.
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Daly, E.M. (2010). Investigation of Localised Centrality Metrics for Collaborative Networks: What Can They Reveal?. In: Coyle, L., Freyne, J. (eds) Artificial Intelligence and Cognitive Science. AICS 2009. Lecture Notes in Computer Science(), vol 6206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17080-5_7
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DOI: https://doi.org/10.1007/978-3-642-17080-5_7
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