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SNA techniques are derived from sociological and social-psychological theories and take into account the whole network (or, in case of very large networks such as Twitter -- a large segment of the network). Thus, we may arrive at results that may seem counter-intuitive -- e.g. that Jusin Bieber (7.5 mil. followers) and Lady Gaga (7.2 mil. followers) have relatively little actual influence despite their celebrity status -- while a middle-of-the-road blogger with 30K followers is able to generate tweets that "go viral" and result in millions of impressions. O'Reilly's "Mining Social Media" and "Programming Collective Intelligence" books are an excellent start for people inteseted in SNA. This book builds on these books' foundations to teach a new, pragmatic, way of doing SNA. I would like to write a book that links theory ("why is this important?", "how do various concepts interact?", "how do I interpret quantitative results?") and practice -- gathering, analyzing and visualizing data using Python and other open-source tools.

Subscriber Reviews

Average Rating: 4.5 out of 5 rating Based on 2 Ratings

"Very good" - by Anna Powell Smith on 07-SEP-2012
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Excellent introduction to the topic - good mixture of interesting examples, theoretical background and practical recipes. Highly recommended.
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"Very Interesting" - by Vishal Singh on 07-APR-2012
Reviewer Rating: 1 star rating2 star rating3 star rating4 star rating5 star rating
I was looking for a book on network effect, how people in the network influence others and then I came across this book. This is indeed a very interesting book, explains complex topic in a very easy manner. Overall, a great reading experience.
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