Web semantica

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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

Ph.D. thesis.

Guillaume Erétéo

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Semantic Social Network Analysis

à Audrey, Mylène, Maman, Papa, Mich et Fab

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Ph.D. thesis.

Guillaume Erétéo

"I hope that while so many people are out smelling the flowers, someone is taking the time to plant some." Herbert Rappaport

iv Semantic Social Network Analysis

Remerciements/Thanks
• A Audrey, Mylène, Maman, et Papa, pour votre amour qui me permet de rêver, de créer et d’avancer chaque jour. • A Michel Buffa et Fabien Gandon, mes directeurs de thèse et amis, pour tout ce que vous m’avez appris et d’inoubliables moments de bonne humeur. • A Olivier Corby pour tes indispensables contributions à mes travaux et tesprécieux enseignements. • A Alain Giboin pour nos fructueuses et intéressantes discussions. • A toutes les personnes avec qui j’ai collaboré au sein du projet ISICIL et des équipes ACACIA, EDELWEISS, KEWI et PUPE d’Orange Labs.

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Ph.D. thesis.

Guillaume Erétéo

Abstract
The outburst of social functionalities in web-based applications has fostered the deployment of a social media landscapewhere people freely contribute, gather and interact with each other. The integration of various means for publishing and socializing allows us to quickly share, recommend and propagate information to our social network, trigger reactions, and finally enrich it. These shared spaces fostered the creation and development of interest communities that publish, filter and organize directories ofreferences in their domains at an impressive scale with very agile responses to changes. In order to reproduce the information sharing success story of the web, more and more social platforms are deployed into corporate intranets. However, the benefit of these platforms is often hindered when the social network becomes so large that relevant information is frequently lost in an overwhelming flow ofactivity notifications. Organizing this huge amount of information is one of the major challenges of Web 2.0 to achieve the full potential of Enterprise 2.0, i.e., the efficient use of Web 2.0 technologies like blogs and wikis within the Intranet. This thesis proposes to help analyzing the characteristics of the heterogeneous social networks that emerge from the use of web-based social applications,with an original contribution that leverages Social Network Analysis with Semantic Web frameworks. Social Network Analysis (SNA) proposes graph algorithms to characterize the structure of a social network and its strategic positions. Semantic Web frameworks allow representing and exchanging knowledge across web applications with a rich typed graph model (RDF), a query language (SPARQL) and schemadefinition frameworks (RDFS and OWL). In this thesis, we merge both models in order to go beyond the mining of the flat link structure of social graphs by integrating a semantic processing of the network typing and the emerging knowledge of online activities. In particular we investigate how (1) to bring online social data to ontology-based representations, (2) to conduct a social network analysisthat takes advantage of the rich semantics of such representations, and (3) to semantically detect and label communities of online social networks and social tagging activities.

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Semantic Social Network Analysis

Résumé
L’explosion des fonctionnalités sociales au sein des applications du Web a favorisé le déploiement d'un panorama de médias sociaux permettant aux utilisateurs de...
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