Maksim Tsvetovat - Social Network Analysis for Startups: Finding connections on the social web
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Copyright 2011 Maksim Tsvetovat and Alexander Kouznetsov
OReilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (.
Nutshell Handbook, the Nutshell Handbook logo, and the OReilly logo are registered trademarks of OReilly Media, Inc. Social Network Analysis for Startups , the image of a hawfinch, and related trade dress are trademarks of OReilly Media, Inc.
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While every precaution has been taken in the preparation of this book, the publisher and authors assume no responsibility for errors or omissions, or for damages resulting from the use of the information contained herein.
Almost every startup company in 2011 uses the word social in their business plansalthough few actually know how to analyze and understand the social processes that can result in their firms success or failure. If you are working in social media, social CRM, social marketing, organizational consulting, etc., you should read this book for insights on how social systems evolve and change, and how to detect what is going on.
Despite the title, the book is not just for startups. In fact, it is a course-in-a-book, encapsulating nearly a semesters worth of theoretical and practical materialread it and you will know enough about social network analysis to be dangerous. If you are a student in the field, we strongly encourage you to seek out and read every paper and book referred to in the footnotes. This will make you conversant in the classic literature of the field and enable you to confidently start your own research project.
If you are of a technical or computer science background, this book will introduce you to major sociological concepts and tie them back into things that can be programmed, and data that can be analyzed. If your background is social sciences or marketing, you may find some of the background material familiar, but at the same time will learn the quantitative and programmatic approaches to understanding humans in a social setting .
This books is written to be accessible by a wide audience. We keep jargon to a minimum, and explain terms as they come along. However, there is a serious amount of technical content (as one expects from an OReilly book).
We expect you to be at least marginally conversant in Pythoni.e., able to write your own scripts, understand the basic control structures and data structures of the language. If you are not yet there, we suggest starting with an online Python tutorial or Head First Python by Paul Barry (OReilly).
We do not cover in detail the process of harvesting data from Twitter, Facebook, and other data sources. Other books in OReillys Animal Guide series provide ample coverage, including Twitter API: Up and Running by Kevin Makice, and Mining the Social Web by Matthew Russell.
This book utilizes open-source Python libraries including NetworkX, NumPy, and MatPlotLib.
NetworkX packages and documentation can be found at http://networkx.lanl.gov/.
Aric A. Hagberg, Daniel A. Schult and Pieter J. Swart, Exploring network structure, dynamics, and function using NetworkX, in Proceedings of the 7th Python in Science Conference (SciPy2008), eds. Gel Varoquaux, Travis Vaught, and Jarrod Millman, pp. 1115, Aug 2008.
NumPy packages and documentation are at http://numpy.scipy.org/.
Oliphant, Travis E. Python for Scientific Computing. Computing in Science & Engineering 9(2007), 10-20 Ascher, D. et al. Numerical Python , tech. report UCRL-MA-128569, Lawrence Livermore National Laboratory, 2001.
MatplotLib can be found at http://matplotlib.sourceforge.net.
Hunter, J.D. Matplotlib: A 2D Graphics Environment. Computing in Science & Engineering 9(2007), 90-95
The following typographical conventions are used in this book:
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This book is here to help you get your job done. In general, you may use the code in this book in your programs and documentation. You do not need to contact us for permission unless youre reproducing a significant portion of the code. For example, writing a program that uses several chunks of code from this book does not require permission. Selling or distributing a CD-ROM of examples from OReilly books does require permission. Answering a question by citing this book and quoting example code does not require permission. Incorporating a significant amount of example code from this book into your products documentation does require permission.
All code, data, and examples can be downloaded from our GitHub repository at https://github.com/maksim2042/SNABook.
We appreciate, but do not require, attribution. An attribution usually includes the title, author, publisher, and ISBN. For example: Social Network Analysis for Startups by Maksim Tsvetovat and Alexander Kouznetsov (OReilly). Copyright 2011 Maksim Tsvetovat and Alexander Kouznetsov, 978-1-449-30646-5.
If you feel your use of code examples falls outside fair use or the permission given above, feel free to contact us at .
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