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.
具體描述
讀後感
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用戶評價
有原版一定要讀原版！
评分噗。。我盡量看完瞭。。這書好像不咋的。。
评分網絡性質&動態變化 入門好書
评分前麵部分是社會網絡與復雜網絡的結閤點,後麵是技術上的東西,很全,很入門...
评分入門。
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