Rowman & Littlefield Publishers
Pages: 330
•
Trim: 6 x 9
978-1-4422-4943-1 • Hardback • March 2016 • $116.00 • (£89.00)
978-1-4422-4944-8 • Paperback • March 2016 • $65.00 • (£50.00)
978-1-4422-4945-5 • eBook • March 2016 • $61.50 • (£47.00)
Daniel Cunningham is associate faculty for instruction in the Defense Analysis Department at the Naval Postgraduate School (NPS) in Monterey, CA. He is also a research associate in the Defense Analysis Department’s Common Operational Research Environment (CORE) Lab.
Sean Everton is an associate professor in the Department of Defense Analysis and the co-director of the CORE Lab at the Naval Postgraduate School (NPS) in Monterey, CA.
Philip Murphy is an assistant professor and the director of the Mixed-methods Evaluation and Training (META) Lab at the Middlebury Institute of International Studies in the Graduate School of International Policy Studies and a research fellow at the Naval Postgraduate School’s CORE Lab.
List of Figures
List of Tables
Introduction
Part I: Introduction to Social Network Analysis
Chapter 1: Social Networks
Chapter 2: Strategic Options for Disrupting Dark Networks
Chapter 3: Collecting, Coding, and Manipulating Social Network Data
Part II: Exploratory Social Network Analysis
Chapter 4: Topographical Features of Dark Networks
Chapter 5: Detecting Subgroups In Networks
Chapter 6: Identifying Central Actors In Networks
Chapter 7: Brokerage within Networks
Chapter 8: Positional Approaches to Analyzing Networks
Part III: Confirmatory Social Network Analysis
Chapter 9: Digging Deeper and Testing Hypotheses
Chapter 10: More Hypothesis Testing: Using Exponential Random Graph Models (Ergms) To Explain Tie Formation
Chapter 11: Longitudinal Analyses of Dark Networks
Part IV: Conclusion
Chapter 12: Lessons Learned
Appendix 1: Data Description And Codebook
Appendix 2: Glossary of Terms
Appendix 3: Analytic Software
References
Index
About the Authors
Finally! Accessible yet comprehensive, Understanding Dark Networks is a much needed and long overdue guide to analyzing covert, and all other, social networks. This is a must-read for anyone even considering using social network analysis effectively.
— Elisa Jayne Bienenstock, college research professor, College of Public Service and Community Solutions, Arizona State University