Visual mining of epidemic networks

Authors:
Stéphan Clémençon;Hector De Arazoza;Fabrice Rossi;Viet-Chi Tran
Affiliations:
Institut Télécom, Télécom ParisTech, LTCI - UMR CNRS 5141, Paris, France;Facultad de Matemática y Computación, Universidad de la Habana, La Habana, Cuba and Laboratoire Paul Painlevé UMR CNRS No. 8524, Université Lille 1, Villeneuve d'Ascq Cedex, Fr ...;Institut Télécom, Télécom ParisTech, LTCI - UMR CNRS 5141, Paris, France;Laboratoire Paul Painlevé UMR CNRS No. 8524, Université Lille 1, Villeneuve d'Ascq Cedex, France
Venue:
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Year:
2011

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Abstract

We show how an interactive graph visualization method based on maximal modularity clustering can be used to explore a large epidemic network. The visual representation is used to display statistical tests results that expose the relations between the propagation of HIV in a sexual contact network and the sexual orientation of the patients.