Statistical Analysis of Networks

This is an interesting book. Models are introduced in the first chapter, and then centralities in the second. Community detection is certainly a popular topic, especially among those working in complex network analysis. And the author is certainly correct that community detection in dynamic networks has received comparatively less exposure. There are models for dynamic networks and extensions of characterizations (like centrality and otherwise) for dynamic networks. Finally, the chapter on sampling is of interest, and not something that is usually covered in network texts. In my opinion the book should have good market appeal. Eric D. Kolaczyk, Boston University, USA -- Eric D. Kolaczyk
The book proposed is a worthwhile one. Network analysis is an active area with a huge amount of work being produced in recent years. The subject of network analysis spans mathematics, probability, statistics, physics and computer science, amongst others. The book focusses on the topics of community detection, dynamic graphs and sampling on graphs. These are all topics of interest to researchers in network analysis and people who analyse network data. Community detection is hugely relevant in applications of network analysis. The book would be useful in providing a formal treatment of many topics of interest to people who use network analysis. The book also focusses on centrality measures which are important, are a full chapter in the book, but downplayed in the description; they should also be emphasised. Brendan Murphy, University College Dublin, Ireland -- Brendan Murphy