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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.
亚马逊主页：http://www.amazon.com/Methods-Network-Analysis-Structural-Sciences/dp/0521600979/ref=cm_cr_pr_product_top
Models and Methods in Social Network Analysis.pdf
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