Semantic Social Network Analysis: A Concrete Case

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Author(s): Guillaume Erétéo (Orange Labs, France), Freddy Limpens (EDELWEISS, INRIA Sophia-Antipolis, France), Fabien Gandon (EDELWEISS, INRIA Sophia-Antipolis, France), Olivier Corby (EDELWEISS, INRIA Sophia-Antipolis, France), Michel Buffa (University of Nice Sophia Antipolis, France), Mylène Leitzelman (University of Nice Sophia Antipolis, France)and Peter Sander (University of Nice Sophia Antipolis, France)
Copyright: 2011
Pages: 35
Source title: Handbook of Research on Methods and Techniques for Studying Virtual Communities: Paradigms and Phenomena
Source Author(s)/Editor(s): Ben Kei Daniel (University of Saskatchewan, Canada)
DOI: 10.4018/978-1-60960-040-2.ch007

Keywords: Information Science Reference / Media & Communications / Social Computing / Virtual Communities & Virtual Reality

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Abstract

In this chapter we present our approach to analyzing such semantic social networks and capturing collective intelligence from collaborative interactions to challenge requirements of Enterprise 2.0. Our tools and models have been tested on an anonymized dataset from Ipernity.com, one of the biggest French social web sites centered on multimedia sharing. This dataset contains over 60,000 users, around half a million declared relationships of three types, and millions of interactions (messages, comments on resources, etc.). We show that the enriched semantic web framework is particularly well-suited for representing online social networks, for identifying their key features and for predicting their evolution. Organizing huge quantity of socially produced information is necessary for a future acceptance of social applications in corporate contexts.

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Semantic Social Network Analysis: A Concrete Case

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