On effectiveness of wiretap programs in mapping social networks

On December 16, 2005, a New York Times article[31] revealed that in the immediate aftermath of the September 11th attacks, the National Security Agency began a broad program of domestic signal intelligence collection. As press reports indicated [28], NSA implemented its new collections program based on the snowball sampling methods, which is generally used in surveying hidden populations and networks. However, snowball method is known to be a biased toward highly connected actors[21] and consequently produces core-periphery networks when these may not necessarily be present. In case of terrorist networks, the last statement is particularly important in light of the “smoking gun” arguments presented by the government. In a further argument, the government argues that wiretaps on suspect terrorist operatives need to be put in place extremely fast and in large quantities, thus overloading the FISA[37] court system. In the use of snowball sampling, overload of information collection system does present a distinct problem due to exponential growth of the number of suspects to be monitored. In this paper, we will focus on evaluating the effectiveness of the wiretapping program in terms of mapping fastchanging networks of a covert organization. By running a series of simulation-based experiments, we are able to give a number of information gathering regimes a fair evaluation based on a consistent criteria. Further, we propose a set of information gathering programs that achieve higher effectiveness then snowball sampling, at a lower cost.