Detecting Leaders in Behavioral networks

Ilham Esslimani 1 Armelle Brun 1, * Anne Boyer 1
* Auteur correspondant
1 KIWI - Knowledge Information and Web Intelligence
LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : The development of the Web engendered the emergence of virtual communities. Analyzing information flows and discovering leaders through these communities becomes thus, a major challenge in different application areas. In this paper, we present an algorithm that aims at detecting leaders in the context of behavioral networks. This algorithm considers the high connectivity and the potentiality of propagating accurate appreciations so as to detect reliable leaders through these networks. This approach is evaluated in terms of precision using a real usage dataset. The results of the experimentation show the interest of our approach to detect TopN behavioral leaders that predict accurately the preferences of the other users. Besides, our approach can be harnessed in different application areas caring about the role of leaders.
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Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Aug 2010, Odense, Denmark. IEEE, pp.281-285, 2010, 〈10.1109/ASONAM.2010.72〉
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https://hal.inria.fr/inria-00581415
Contributeur : Armelle Brun <>
Soumis le : mercredi 30 mars 2011 - 17:54:17
Dernière modification le : mardi 24 avril 2018 - 13:33:02

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Ilham Esslimani, Armelle Brun, Anne Boyer. Detecting Leaders in Behavioral networks. Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Aug 2010, Odense, Denmark. IEEE, pp.281-285, 2010, 〈10.1109/ASONAM.2010.72〉. 〈inria-00581415〉

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