Chapter 1. Introduction
Analyzing Relationships to Understand People and Groups
From Relationships to Networks—More Than Meets the Eye
Social Networks vs. Link Analysis
The Power of Informal Networks
Terrorists and Revolutionaries: The Power of Social Networks

Chapter 2. Graph Theory—A Quick Introduction
What Is a Graph?
Graph Traversals and Distances
Graph Distance
Why This Matters
6 Degrees of Separation is a Myth!
Small World Networks

Chapter 3. Centrality, Power, and Bottlenecks
Sample Data: The Russians are Coming!
Centrality
What Can’t Centrality Metrics Tell Us?

Chapter 4. Cliques, Clusters and Components
Components and Subgraphs
Subgraphs—Ego Networks
Triads
Cliques
Hierarchical Clustering
Triads, Network Density, and Conflict

Chapter 5. 2-Mode Networks
Does Campaign Finance Influence Elections?
Theory of 2-Mode Networks
Expanding Multimode Networks

Chapter 6. Going Viral! Information Diffusion
Anatomy of a Viral Video
How Does Information Shape Networks (and Vice Versa)?
A Simple Dynamic Model in Python
Coevolution of Networks and Information

Chapter 7. Graph Data in the Real World
Medium Data: The Tradition
Big Data: The Future, Starting Today
“Small Data”—Flat File Representations
“Medium Data”: Database Representation
Working with 2-Mode Data
Social Networks and Big Data
Big Data at Work

Appendix Data Collection
A Note on the Ethics of Data Collection
The Old-Fashioned Way
Mining Server Logs
Mining Social Media Sites
Twitter Data Collection
Facebook

Appendix Installing Software
Why (We Love) Python?
Exploratory Programming
Python
IPython
NetworkX
matplotlib

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