Analyzing Social Networks

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

Written by a stellar team of experts, Analyzing Social Networks is a practical book on how to collect, visualize, analyze and interpret social network data with a particular emphasis on the use of the software tools UCINET and Netdraw.

The book includes a clear and detailed introduction to the fundamental concepts of network analyses, including centrality, subgroups, equivalence and network structure, as well as cross-cutting chapters that helpfully show how to apply network concepts to different kinds of networks.

Written using simple language and notation with few equations, this book masterfully covers the research process,
· The initial design stage
· Data collection and manipulation
· Measuring key variables
· Exploration of structure
· Hypothesis testing
· Interpretation

This is an essential resource for students, researchers and practitioners across the social sciences who want to use network analysis as part of their research. 
A companion website is available  sites.google.com/site/analyzingsocial...

Genres: Textbooks, Nonfiction

304 pages, Hardcover

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.