Computational Statistical Advances in Social Network Analysis
Alberto Caimo (University of Lugano, Switzerland)
Substantial developments in statistical methods are having a profound impact on research on social network. Statistical models are at the core of efforts in understanding the relational processes underlying social network formation and evolution. In particular, computational methods provide fertile grounds for further progress on scaling current methods to large networks. This session will focus on major recent trends in statistical network analysis featuring a blend of computational and modeling approaches to network data.
We are seeking to attract papers that attempt to bring the new generation of computational techniques to bear on central problems in the analysis of social networks. The session is expected to provide a rich opportunity for researchers currently working in this area to meet, share and discuss the most recent results.