Analyzing Social Networks

by Stephen P. Borgatti, Martin G. Everett, Jeffrey C. Johnson

Designed to walk beginners through core aspects of collecting, visualizing, analyzing, and interpreting social network data, this book will get you up-to-speed on the theory and skills you need to conduct social network analysis. Using simple language and equations, the authors provide expert, clear insight into every step of the research process―including basic maths principles―without making assumptions about what you know. With a particular focus on NetDraw and UCINET, the book introduces relevant software tools step-by-step in an easy to follow way. In addition to the fundamentals of network analysis and the research process, this  Second Edition focuses Supported by new chapter exercises, a glossary, and a fully updated companion website, this text is the perfect student-friendly introduction to social network analysis. 

Genres: Textbooks, Nonfiction

384 pages, Paperback

First published May 13, 2013

Reviews

[Janet · Rating 3 out of 5]

This primer provides decent examples and is a good place to start for the practical methods and analysis aspects to studying social networks with suggested references for deeper reading. Some definitions seemed a bit circular and abstract making them difficult to grasp. Good figures and tables help to elucidate examples.

[erin · Rating 4 out of 5]

pretty accessible and useful. especially if you are going to use UCINET, but even if you are not.

[Scott Pearson · Rating 5 out of 5]

With so much Internet data available through social media, social networks have entered the popular consciousness. They have long been used by social scientists to analyze complex research questions, so the theories are robust and tested by time. Still, many of us worry about reading about a technical topic that’s not in our traditional field, but this book proves accessible and engaging. It introduces the topic while exciting readers’ minds with relevant concepts that can translate directly into analytic value.

Notably, this book now exists in a new third edition, but I bought the second edition right as the third edition was released. The new version seems to have more use cases, but the theory has not advanced that much since 2018.

Reading this book, I was pleasantly surprised with how quickly I could translate reading a paragraph into an idea to pursue with my data. I took a good page of notes that I now need to review to formulate into action items. Even though social science and social network analysis do not lie in my formal training, my eyes only rarely glazed over while reading a paragraph. Instead, I now see my work in a new light with much potential to extract analytic insights.

This book is suitable for a late undergraduate course or graduate school offering. Little mathematical knowledge is required, though some statistics are presumed to translate findings into research. A few basic mathematical formulae are presented, but nothing is derived. It’s accessible so that translatable concepts take the fore. Curious readers should find relevant insights for their projects.

[Ted Graham · Rating 3 out of 5]

A good textbook a methodology. I found it very helpful as I began exploring an entirely new field of research for myself. The writing was clear and concise, but very well-supported will great examples.

[ACRL]

Read by ACRL Member of the Week Marie R. Kennedy. Learn more about Marie on the ACRL Insider blog.

[Marianne Sarkis · Rating 5 out of 5]

I've worn out my copy. I have used it so much in doing SNA. It's so good to finally have updated instructions for UCINET.

[Marianne Sarkis · Rating 5 out of 5]

I have worn out my copy. So good to have some updated instructions for UCINET.

[Ann Deraedt]

Quit technical. First 2 chapters ok, but afterwords not really "and now i will finish it". So I finished at chapter 4.