Borgatti, S.P., Everett, M.G. and Johnson J.C. (2013) Analyzing social networks

This book takes the reader on a tour of key theoretical concepts in social network analysis. It is divided into four sections: introduction, research methods, core concepts and measures and a final section which deals with what the writers describe as ‘three cross-cutting chapters’ on ‘affiliation type data’, ‘large networks’ and ‘ego network data’. Although primarily theoretical, the book refers to interesting empirical work across the social sciences and health care in order to illustrate core concepts. It introduces readers to software – UCINET and NetDraw – which they can use to analyse and visualise network data but refers to a dedicated website for readers who require a software tutorial.

There is much to commend in this book. The authors provide a clear introduction to graph theory and matrix algebra for non-mathematicians. There is also an interesting introduction to core concepts like ‘centrality’, ‘sub-group’ and ‘equivalence’ and a fascinating discussion of how hypothesis testing is possible with network data when the assumptions of standard inferential tests are violated. The authors also provide invaluable advice on how best to lay out network diagrams in order to make interpretation easier.

However, I think that how information is presented may need to be reviewed. The authors assume that readers are familiar with research terminology without necessarily defining their terms. Although this is a reasonable assumption if the book is for established researchers, beginners may need to refer to an introductory research methods textbook in order to take full advantage of the material. Borgatti et al. also state that a sequential reading of each chapter isn’t needed although this suggestion doesn’t work for readers who assume that a book will begin with straightforward material before moving to advanced topics. A glossary would be useful.

This is an informative book for established social researchers with some prior exposure to social network analysis. Aspirant social network analysts may find the book a little too advanced.

Review originally published in Research Matters, March 2014