This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Statistical Network Analysis: Models, Issues, and New Directions held in Pittsburgh, PA, USA in June 2006 as associated event of the 23th International Conference on Machine Learning, ICML 2006.

The 12 revised full papers and 4 invited lectures presented together with the summary of the closing panel discussion were carefully revised and selected during two rounds of reviewing and improvement from the presentations at the workshop. The papers focus on probabilistic methods for network analysis, paying special attention to model design and computational issues of learning and inference. The workshop brings together statistical network modeling researchers from different communities to create and motivate novel modeling approaches, diverse applications, and new research directions.