- Paperback: 192 pages
- Publisher: O'Reilly Media; 1 edition (October 10, 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: 10 customer reviews
- Amazon Best Sellers Rank: #668,938 in Books (See Top 100 in Books)
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Social Network Analysis for Startups: Finding connections on the social web 1st Edition
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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.
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.
Top customer reviews
The downside: assumes you have a decent knowledge of Python. If you don't, go learn that first.
The upside: extremely detailed and well-illustrated principles for doing social network analysis. The applications are tangible and well-explained.
There is a learning curve involved but it's worth the persistence. If you want to get started on quantitative analysis for social networks, you should pick up this book.
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
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.