Semantic Social Network Analysis
Building (2009)
- arXiv: 0904.3701
Available from arxiv.org
or
Abstract
Social Network Analysis (SNA) tries to understand and exploit the key features of social networks in order to manage their life cycle and predict their evolution. Increasingly popular web 2.0 sites are forming huge social network. Classical methods from social network analysis (SNA) have been applied to such online networks. In this paper, we propose leveraging semantic web technologies to merge and exploit the best features of each domain. We present how to facilitate and enhance the analysis of online social networks, exploiting the power of semantic social network analysis.
Available from arxiv.org
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Semantic Social Network Analysis
Semantic Social Network
Analysis
Ph.D. thesis
Defended on the 11th of April 2011 by Guillaume Erétéo
Jury:
• President : Fabrice Rossi (Telecom ParisTech)
• Reporters : Marie-Aude Aufaure (Ecole Centrale Paris)
Pascale Kuntz (University of Nantes)
• Directors : Michel Buffa (I3S, University of Nice - Sophia Antipolis)
Fabien Gandon (INRIA Sophia Antipolis)
• Invited: Patrick Grohan (Orange Labs - Sophia Antipolis)
Orange Labs
Telecom ParisTech
INRIA Sophia Antipolis – Méditerranée
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Ph.D. thesis. Guillaume Erétéo
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