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Reviewer: Claudia Roda

Social network analysis has recently been applied to fields as diverse as history, biology, business administration, medicine, and political science. In recent years, several software tools (see Huisman and van Duijn [1] for a review) have been developed to support the many network analytic techniques that form the growing body of work that makes up the methodological foundations of social networks theory. The authors of this new book guide their readers through a well-selected and clearly organized set of topics and techniques necessary for an understanding of the relationships between and among, for example, individuals, organizations, or nation states. Concepts are always explained in the context of real-world examples, and the theory is integrated with applications using the software package Pajek. While the book does not seek to provide a complete and thorough overview of all issues and techniques in social network analysis, or an inclusive guide to the Pajek software, it addresses what the authors indicate to be the "three major research topics in social network analysis": cohesion, brokerage, and ranking. Block modeling is also examined as "an advanced technique [that] integrates the three research topics." Compared to other books frequently used to introduce social network analysis [2,3], this book places much more emphasis on applications, and presents all concepts without using mathematical notations. In this sense, it is ideal as an introduction to the subject for a wide audience, which may not be interested in mathematical properties, or in developing algorithms (if you are interested in these latter aspects, Wasserman and Faust's book [3] may be more suitable). Notwithstanding the lack of formal notation, rigor in the introduction of concepts is skillfully maintained by supplying precise verbatim definitions. The glossary supplied at the end of the book is also rigorous and helpful. While hypothesis testing falls completely outside the book's scope, its focus is on network exploration through techniques for network manipulation and visualization, and the software used is well suited for this purpose. The authors have made an effort to explicitly render some of the assumptions underlying the models used, as well as most of the assumptions underlying the manipulation techniques. One of the strengths of this book is its smooth integration of theory presentation and instructions for the use of related functions in Pajek (opening the way for a more in-depth and personalized exploration of the various concepts). However, the sections describing the software are well separated from the coverage of theory and the examples, so an uninterested reader could skip them. The bibliography, although not extensive, is adequate. Further readings are placed at the end of each chapter, but references are not generally given in the main text, which makes it harder for the reader to connect to existing literature while reading. The three appendices ("Getting Started with Pajek," "Exporting Visualizations," and "Shortcut Key Combinations"), together with the "Index of Pajek Commands," supply the essential reference material to work with Pajek. Overall, the book reads very well, and introduces important and sometimes complex concepts in a very clear manner. By analyzing real-world examples and discussing the advantages and limitations of the various techniques, the book stimulates the reader's curiosity and provides incentive for reflection. It also supplies the essential tools for further applications of social network analysis. Online Computing Reviews Service