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This book is written to introduce the relevant “concepts and techniques for recognizing patterns in social media, political groups, companies, cultural trends, and interpersonal networks. You’ll also learn how to use Python and other open source tools—such as NetworkX, NumPy, and Matplotlib—to gather, analyze, and visualize social data. This book is the perfect marriage between social network theory and practice, and a valuable source of insight and ideas” (Tsvetovat, 2011).

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Chengjun Wang and Jing Liu participated in the translation of the book Social Network Analysis for Startups written by two computer scientists (Maksim Tsvetovat and Alexander Kouznetsov) into Chinese. Currently, the book has been published by China Machine Press in June 1, 2013.

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To build the network analysis on Python makes this little book quite remarkable. Although classic software has done a good job in traditional network analysis. It is restrained by the data size, and almost impossible for the users to program new functions flexibly. However, using Python which is a mainstream script programming language, you can develop new functions to finish you job efficiently for you are standing on the shoulder of computer science. For example, in this book, the method of network sampling on the social web will be briefly talked about, and the simulation of information diffusion has been extensively discussed in chapter 6. That’s one small step for [a] book, one giant leap for both classic social network analysis and the startups.

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