Social Network Analysis for Startups: Finding Connections on the Social Web

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"O'Reilly Media, Inc.", Oct 6, 2011 - Computers - 174 pages
2 Reviews

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
  

What people are saying - Write a review

Review: Social Network Analysis for Startups: Finding connections on the social web

User Review  - Vuk Trifkovic - Goodreads

Good introduction to graph theory in general, but nothing spectacular. Still a very good intro and some good Russian stories & jokes... Read full review

Review: Social Network Analysis for Startups: Finding connections on the social web

User Review  - Wael Al-alwani - Goodreads

Truly amazing book. It introduces startups (= beginners) to the great world of social network analysis, a sub filed in a wider field called computational social science. The book inspired me with many ideas. Very recommended read. Read full review

Contents

Chapter 1 Introduction
1
Chapter 2 Graph TheoryA Quick Introduction
19
Chapter 3 Centrality Power and Bottlenecks
39
Chapter 4 Cliques Clusters and Components
61
Chapter 5 2Mode Networks
93
Chapter 6 Going Viral Information Diffusion
109
Chapter 7 Graph Data in the Real World
137
Appendix A Data Collection
161
Appendix B Installing Software
171
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About the author (2011)

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.

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