I recently published a book ("Disrupting Dark Networks") on the use of social network analysis to disrupt or destabilize dark networks, that is, groups that seek to conceal themselves and their activities from authorities. While the term is typically used to refer to terrorists, gangs, drug cartels, arms traffickers, and so on, it can also refer to benign groups, such as Zegota, the predominantly Roman Catholic underground organization that helped Jews survive Nazi-occupied Poland during WWII.
What is social network analysis (SNA)? For starters, it's not the same as tweeting messages or checking-in on Facebook although the pattern of tweets and the connections between friends can be analyzed using SNA. Instead, SNA is a collection of theories and methods that assumes that the behavior of actors (whether individuals, groups, or organizations) is affected by their ties to others and the networks in which they are embedded. Rather than viewing actors as unaffected by those around them, SNA assumes that we are social beings whose interaction patterns affect what we do, say, and believe. We know, for example, that people who have ties to people involved in a church, synagogue, temple, mosque, etc. are much more likely to join that church, synagogue, temple, mosque than are people who don't have such ties. The same is also true of social movements, such as the Civil Rights movement or the Global Salafi Jihad. People were/are far more likely to join if they know someone who is already involved.
In short, social networks not only enable and constrain behavior but that they are also chock-full of meaning, and as such help us make sense of our world, shape our preferences, and influence the choices we make. That's why a primary goal of SNA has been to develop metrics that help analysts gain a better understanding of a particular network’s structural features. And although organizational theorists tend to explore such questions with the goal of identifying factors that will help strengthen organizations, those who study dark networks are generally more interested in identifying those aspects that will undermine them.
Take, for instance, the graph at the top of this post. It presents the social network of the characters in the novel, Les Misérables, which comes with the SNA software package, Gephi. A tie is drawn between two characters (nodes) if they co-appear in the novel, node color indicates the various subgroups to which each character belongs (determined by a clustering algorithm), and node size reflects the number of connections each character has to other characters. Not surprisingly, the ex-convict Jean Valjean, the novel's central character, is the largest node. Not surprisingly (since he spends a good deal of the novel on the run from Inspector Javert), he is a cluster unto himself (he's the only red-colored node), which suggests that he is something of a loner. That said, he is closely tied to his adopted daughter, Cosette, and her (eventual) husband, Marius Pontmercy. He is also tied to Inspector Javert, who for most of the novel, is obsessed with putting Valjean behind bars.
The network, of course, is not just a dark network; it is, instead, a mix of light and dark networks and what is light and what is dark depends largely on one's perspective. However, if it were a dark, one could possibly use SNA to disrupt it. For example, if one was interested in influencing Valjean (in a negative way), he or she would probably want to target Cosette or Marius if they couldn't target Valjean directly. Or again, if you look closely at the graph, you'll see that the light green cluster on the right is composed primarily of the "Friends of the ABC," which is a revolutionary student club involved in the Paris uprising of 1832, clearly a dark network in the eyes of French authorities. Because of the interconnectedness of the group, simply removing one person (e.g., the leader, Enjolras) probably wouldn't cause it to fall apart. Instead, everyone in the group would need to be silenced (a tall order) or the group would need to be isolated (e.g., by discrediting it) in order to render it ineffective.
I've posted previously on social networks and how they can be used to disrupt terrorist networks ("Social Networks and the Fight Against Terrorism"). In that post I also reference an article in which my co-author (Nancy Roberts) explore the various ways that SNA can be used to disrupt terrorist networks ("Strategies for Combating Dark Networks"). The article's abstract is as follows:
Our goal in this paper is to explore two generic approaches to disrupting dark networks: kinetic and non-kinetic. The kinetic approach involves aggressive and offensive measures to eliminate or capture network members and their supporters, while the non-kinetic approach involves the use of subtle, non-coercive means for combating dark networks. Two strategies derive from the kinetic approach: Targeting and Capacity-building. Four strategies derive from the non-kinetic approach: Institution-Building, Psychological Operations, Information Operations and Rehabilitation. We use network data from Noordin Top’s South East Asian terror network to illustrate how both kinetic and non-kinetic strategies could be pursued depending on a commander’s intent. Using this strategic framework as a backdrop, we strongly advise the use of SNA metrics in developing alterative counter-terrorism strategies that are context- dependent rather than letting SNA metrics define and drive a particular strategy.