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Models and Methods in Social Network Analysis (Structural Analysis in the Social Sciences) Hardcover – 7 Feb 2005

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4 out of 5 stars 3 reviews from the U.S.

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Book Description

This book consists of review articles by leading methodologists, all commissioned exclusively for this volume. The book will complement the classic text by Wasserman and Faust, Social Network Analysis: Methods and Applications (also available from Cambridge University Press).

About the Author

Peter J. Carrington is Professor of Sociology at the University of Waterloo. His main teaching and research interests are in the criminal and juvenile justice systems, social networks, and research methods and statistics. He has published articles in the Canadian Journal of Criminology and Criminal Justice, the American Journal of Psychiatry, the Journal of Mathematical Sociology, and Social Networks. He has most recently been involved in several evaluation studies for the Department of Justice Canada. He is currently doing research on police discretion, criminal and delinquent careers and networks, and the impact of the Youth Criminal Justice Act on the youth justice system in Canada.

John Scott is Professor of Sociology at the University of Essex. An active member of the British Sociological Association, he served as its President from 2001 until 2003. He has written more than fifteen books, including Corporate Business and Capitalist Classes (1997), Social Network Analysis (1991 and 2000), Sociological Theory (1995), and Power (2001). With James Fulcher he is the author of the leading introductory textbook Sociology (1999 and 2003). He is a member of the Editorial Board of the British Journal of Sociology and is an Academician of the Academy of Learned Societies in the Social Sciences.

Stanley Wasserman is Professor of Psychology, Statistics, and Sociology at the University of Illinois-Champaign. He has done research on methodology for social networks for almost thirty years. He has edited books on the subject, including Advances in Social Network Analysis: Research in the Social and Behavioral Sciences (1994), and Social Network Analysis: Methods and Applications (1994). His work is recognized by statisticians as well as social and behavioral scientists worldwide. He is currently Book Review Editor of Chance, and an Associate Editor of the Journal of the American Statistical Association and Psychometrika. He has also been a very active consultant, and is currently Chief Scientist of Visible Path, an organizational network software firm.

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Amazon.com: 4.0 out of 5 stars 3 reviews
1 of 1 people found the following review helpful
5.0 out of 5 stars Good reference 2 Nov. 2012
By Zhongjian Lin - Published on Amazon.com
Format: Paperback Verified Purchase
A comprehensive book coauthored by several leading researchers and provide wide analyses on social network. A good review book from enormous dimensions.
12 of 12 people found the following review helpful
4.0 out of 5 stars Put on your technical hat. This is advanced math more than a social network research guide. 8 May 2007
By D. Stuart - Published on Amazon.com
Format: Paperback
Social Network Analysis is taking off. in 1932 the sociologist Moreno was the first to draw a social network diagram, yet while the thinking has been seductive the technical capability of generating social network maps has only recently arrived on the researcher's desktop. Suddenly, as it were, many different sciences (social science, organisational research, market research, environmental research) are connecting the dots.

Social network analysis is mathematically vastly different from normal statistical methods. A whole new language is used - and concepts such as "betweenness" or "centrality" correctly convey the spatial nature of SN analysis.

This volume of 13 papers on the topic includes the perspectives of social scientists, through to cutting-edge SN mathematicians, and to be honest I come more from the former category. I'm a market research analyst and found the more intensely mathematical chapters, replete with formulae, simply beyond my grasp. So a warning for readers of my persuasion: you'll need to put on your technical hat.

That said, there is more than enough grist here for a lay person such as myself to learn the basics of Social Network Analysis and to understand many of the new dynamics of this field. I particularly recommend Linton Freeman's chapter of graphical techniques because it makes a warm link between the science and art of this emerging field.

The last chapter also more than makes the price of admission well worthwhile because it reviews available SN softwares (this book was published in 2005 so it is quite contemporary) and our small analytical firm has been able to invest in a good product. We now use the book as our technical support as we learn the unique and illuminating characteristics of social network analysis - in organisational research, and in some innovative work we're now able to do in market research. This volume is practical help.

Our society is increasingly networked through mobiles, internet and other layers of social connection. For social, organisational and market researchers this field is vital. I can therefore recommend this volume as a guidebook. If I found it valuable (despite being somewhat difficult,) you readers with a math degree will find it even more fascinating. Strongly recommended if you're getting into the SN field.

PS. On a broader front, let me also recommend:Six Degrees: The Science of a Connected Age (Open Market Edition)
2 of 2 people found the following review helpful
3.0 out of 5 stars Missing just a few things... 14 Dec. 2010
By Angus Vantoch-wood - Published on Amazon.com
Format: Paperback
Being fairly new to Social Network Analysis, I was suggested this book as an all round read and have to say that it comes in handy from a referencing point of view. It's fairly straight forwards in the things that it explains and covers a lot of the necessary theory of things for a good understanding of SNA. Unfortunately, as it's built from a collection of papers, it does miss some of the very key factors that a beginner in the field would really need. For example, there is a whole chapter on group centrality measures but nothing at all devoted to the understanding and calculation of individual centrality measures of actors (including eigenvector centrality which is a tricky concept). It also misses information about gathering and hypothesising with SNA data which in fairness, it's not pretending to be a book on but would have been good.

If you've got a lot of books on SNA and want to be up to speed with the latest techniques then this is an excellent book, (and you probably already own it!) If however, you're looking for a couple of introductory books on the field and are only planning to get one or two then this one alas probably won't cover all your bases.
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