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.
Cite
@article{arxiv.1210.5694,
title = {Visual Mining of Epidemic Networks},
author = {Stéphan Clémençon and Hector De Arazoza and Fabrice Rossi and Viet Chi Tran},
journal= {arXiv preprint arXiv:1210.5694},
year = {2012}
}