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.
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前面部分是社会网络与复杂网络的结合点,后面是技术上的东西,很全,很入门...
评分入门。
评分前面部分是社会网络与复杂网络的结合点,后面是技术上的东西,很全,很入门...
评分前面部分是社会网络与复杂网络的结合点,后面是技术上的东西,很全,很入门...
评分网络性质&动态变化 入门好书
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