Clearly social network analysis can be applied to the study of covert networks (Sparrow, 1991). However, it would be a mistake to assume that in order to understand these networks we just need to “connect the dots” and then isolate the “key” actors who are often defined in terms of their “centrality” in the network. To an extent, this is right, as in the case of bridging members embedded within patron-client networks. However, within covert networks such as Cosa Nostra, this assumption belies the difficulty of “connecting the dots” in terms of mining vast quantities of information, pattern matching on characteristics for mafiosi who often go under multiple aliases, and still ending up with information the may be intentionally misleading, inaccurate, out-of-date, and incomplete. Further, this belies the difficulty in “knowing” who is the most central when you have at best only a sample of the network.
Finally, and critically, this approach does not contend with the most pressing problem—the underlying network is dynamic. Just because you isolate a key actor today does not mean that the network will be destabilized and unable to respond. Rather, it is possible, that isolating such an actor may have...
... middle of paper ...
...ertise is critical. This is particularly applicable to Cosa Nostra considering that, according to Gambetta, mafiosi are highly specialized according to specific tasks. (Gambetta 67)
There are two key themes underlying these results. First, it is easier to determine how to impact the performance or the flow of information through an organization than it is to determine exactly how it will adapt. It is easier to destabilize a network than to determine what new goals it will form or new tasks it will take on. This is a function of our lack of knowledge about the processes of adaptation other than learning. Second, the relative impact of destabilization strategies strongly depends on the underlying organizational architecture, that is, on the meta-network itself. As such, a key interpretation of these results is in terms of destabilizing different classes of networks.
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