Social Network Analysis (Anglais) Broché – 6 décembre 2012
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Description du produit
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Biographie de l'auteur
John Scott is Professor of Sociology and Pro Vice-Chancellor for Research at Plymouth University. He was previously Professor of Sociology at Essex University and Leicester University. He is a Fellow of the British Academy, an Academician of the Academy of learned Societies in the Social Sciences, and a Fellow of the Royal Society of Arts. An active member of the British Sociological Association, he has held the posts of Secretary, Treasurer, Chairperson, and President. His most recent publications are Conceptualising the Social World (Cambridge University Press, 2011), The Sage Handbook of Social Network Analysis (edited with Peter Carrington, Sage Publications, 2011), and Sociology (with James Fulcher, Oxfords University Press, 2011). His current work on the history of British sociology will appears as Envisioning Sociology. Victor Branford, Patrick Geddes, and the Quest for Social Reconstruction (with Ray Bromley, SUNY Press, 2013).
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Still, this is a seminal work for all that wish to know more about social network analysis.
Like the author says, this is more of a guidebook than something you can read cover to cover. It's intended as a reference for graduate-level social science research, and it shows. If you purchase this book expecting to use it as a how-to for applied market research, you're going to be sorely disappointed.
Overall, I found this book quite informative. It reads like a research methodology textbook (as you'd expect from a book published by SAGE) -- that is, dry and fraught with discussion of theory -- but to the right audience this would be quite valuable.
The back cover proclaims that this edition "incorporate[s] the most important and cutting-edge developments in the field"; I don't know about cutting-edge, but it does discuss a lot of important methodological concepts implicated in mass comm research, and I'd certainly recommend this to any MA student who plans to study new media.
That said, I think this book could be improved by a bit more depth. It's clearly aimed at graduate (or professorial) researchers; it's focused on academic research, and it's much too high-level for undergraduates. But everything in this book is more of a primer than a thorough discussion of the material. That's not to say it's a bad book -- I'm still going to recommend it to my former colleagues -- but like I said, it's a starting point for the discussion.
It's not that type of book.
This is a very high level theory book that also includes some exercises for analyzing data sets.
By the authors own admission, "This book is a guide or handbook and not a text to read in one sitting."
This is almost like a statistics book, that provides methods on how to interpret attributes and relational connections. This is not a book about methods for boosting your numbers, but simply a resource for high level thinking of relationship data and collection methods.
Not what I was expecting, but the author has put in a lot of effort. Great for the academic, but an uphill battle for the layman.
This is about a sociologist’s view of social networks, that is all the varying groups that humans form. Quoting the author, social network analysis “ comprises a broad approach to sociological analysis and a set of methodological techniques that aim to describe and explore the patterns apparent in the social relationships that individuals and groups form with each other”.
We’re humans and we form networks, which by their very nature are social. Family. Friends. Co-workers. Tribe, Clan. State. Nation.
But how to measure those networks? How to describe the dynamics?
Statistically. Mathematically. All things, including behaviors, can be reduced to numbers.
And essentially, this is the introductory text to showing you how.
It is very dense, but well-written. It is most certainly intended to be used as a text, but the person who is interested in statistics and the operation of social networks, will find the book interesting, if not fascinating.
I can’t really judge it as a text. My observation is that it would take a talented instructor to make this material come alive to a presumably uninterested student. But as that self-described reader with an interest in statistics and learning how people interact in their networks, it’s an enthralling, if difficult, read.