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Social Network Analysis for Startups: Finding connections on the social web [Paperback]

Maksim Tsvetovat , Alexander Kouznetsov
4.2 out of 5 stars  See all reviews (5 customer reviews)

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Book Description

October 7, 2011

Does your startup rely on social network analysis? This concise guide provides a statistical framework to help you identify social processes hidden among the tons of data now available.

Social network analysis (SNA) is a discipline that predates Facebook and Twitter by 30 years. Through expert SNA researchers, you'll learn 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.

  • Discover how internal social networks affect a company’s ability to perform
  • Follow terrorists and revolutionaries through the 1998 Khobar Towers bombing, the 9/11 attacks, and the Egyptian uprising
  • Learn how a single special-interest group can control the outcome of a national election
  • Examine relationships between companies through investment networks and shared boards of directors
  • Delve into the anatomy of cultural fads and trends—offline phenomena often mediated by Twitter and Facebook

Frequently Bought Together

Social Network Analysis for Startups: Finding connections on the social web + Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites + Programming Collective Intelligence: Building Smart Web 2.0 Applications
Price for all three: $74.25

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Editorial Reviews

From the Author

This book is designed as a first exposure to the field of Social Network Analysis -- it will get the reader from wondering "what is this about?" to performing a complete analytics project within a few days of reading, doing the exercises and playing with the data.  
This book's intention is to provide very accessible guide to practical analysis, and a starting point on a long exploration of social networks online, in business, and in government. 

About the Author

Maksim Tsvetovat is an interdisciplinary scientist, a software engineer, and a jazz musician. He has received his doctorate from Carnegie Mellon University in the field of Computation, Organizations and Society, concentrating on computational modeling of evolution of social networks, diffusion of information and attitudes, and emergence of collective intelligence. Currently, he teaches social network analysis at George Mason University. He is also a co-founder of DeepMile Networks, a startup company concentrating on mapping influence in social media. Maksim also teaches executive seminars in social network analysis, including "Social Networks for Startups" and "Understanding Social Media for Decisionmakers".

Alex Kouznetsov is an open-source software developer. He has developed a number of social network analysis tools for the industry, from large-scale data collection to online analysis and presentation tools.


Product Details

  • Paperback: 192 pages
  • Publisher: O'Reilly Media (October 7, 2011)
  • Language: English
  • ISBN-10: 1449306462
  • ISBN-13: 978-1449306465
  • Product Dimensions: 7 x 0.4 x 9.2 inches
  • Shipping Weight: 8 ounces (View shipping rates and policies)
  • Average Customer Review: 4.2 out of 5 stars  See all reviews (5 customer reviews)
  • Amazon Best Sellers Rank: #248,251 in Books (See Top 100 in Books)

More About the Author

Maksim Tsvetovat is an interdisciplinary scientist, a software engineer, and a jazz musician. He has received his doctorate from Carnegie Mellon University in the field of Computation, Organizations and Society, concentrating on computational modeling of evolution of social networks, diffusion of information and attitudes, and emergence of collective intelligence.

Currently, he teaches social network analysis at George Mason University.

He is also a co-founder of DeepMile Networks, a startup company concentrating on mapping influence in social media. Maksim also teaches executive seminars in social network analysis, including "Social Networks for Startups" and "Understanding Social Media for Decisionmakers".

Customer Reviews

4.2 out of 5 stars
(5)
4.2 out of 5 stars
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Most Helpful Customer Reviews
7 of 7 people found the following review helpful
4.0 out of 5 stars Social Network Analysis for Startups October 14, 2011
By tjain
Format:Paperback
One of the hot topics in business is Social Media and its effect on it. This has led to growth in Social Network Analysis.

As the name suggest book Social Network Analysis for Startup deals Social Networks' Analysis but not for startups but for Beginners. If we take the name thing apart book is excellent introduction of Social Network Analysis in very simple language. Book not only talks theory but also give hands on practice sessions on the concepts using python (to be very precise NetworkX - [...]).

Book consists of seven chapters. Chapter one and two focuses on Basics of Graph theory. Chapter three, four and five talk about metrics in a Social Network. Chapter six discusses how "a thing" goes viral and what the characteristics of phenomena are. Final Chapter talks about volume of data to be dealt with in Analysis of Social Networks. Appendix A is about ethics involved while doing SNA and listing of APIs and software which can help in SNA. Appendix B is about installation of software (Python and more).

Book might have discussed NetworkX more in details to help understand the library in detail. I strongly recommend reading NetworkX documentation along with book.

With all of its flaws, book is fantastic for beginners in field of SNA. This book certainly be on my bookshelf for long time.
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1 of 1 people found the following review helpful
5.0 out of 5 stars Excellent representation of the graph theory May 13, 2012
Format:Paperback|Amazon Verified Purchase
This book is well thought out and is useful both as an overview of network analysis and as a practical application of the theory. I really liked explanations of the graph theory and ideas behind the examples, so the examples illustrate a deeper meaning than just simple exercises.
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5.0 out of 5 stars a very good introduction December 25, 2012
Format:Paperback|Amazon Verified Purchase
The book introduces SNA in a very understandable manner.
It has many examples in python that makes the subject accessible.
The main author Maksim Tsvetovat has many video lectures on the net that helped me a lot.
The best book I own in terms of value / pages
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