Understanding Dark Networks: A Strategic Framework for the Use of Social Network Analysis

Dark networks are the illegal and covert networks (e.g, insurgents, jihadi groups, or drug cartels) that security and intelligence analysts must track and identify to be able to disrupt and dismantle them. This text explains how this can be done by using the Social Network Analysis (SNA) method. Written in an accessible manner, it provides an introduction to SNA, presenting tools and concepts, and showing how SNA can inform the crafting of a wide array of strategies for the tracking and disrupting of dark networks.

Table of Contents:
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

About the Author :
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.

Review :
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. Cunningham, Everton, and Murphy’s book is most relevant for practitioners, researchers, or anyone seeking to understand dark networks. Practitioners often worry that SNA is difficult to learn and comprehend, but through Cunningham’s easily accessible writing, anyone can understand and apply it after reading this book. Understanding Dark Networks would also have utility for teaching SNA to undergraduates, graduate, postgraduate students in many fields. The early chapters are accessible to anyone, but the last section requires baseline statistical knowledge. Social Network Analysis represents the future of dark network analysis, ranging from jihadist groups to gangs. All intelligence analysts and researchers would see their research value increase with an in-depth understanding of SNA. Understanding Dark Networks should be an essential read for any practitioner or security scholar interested in learning or furthering their knowledge of SNA.