A common terror-fighting tactic has been using drone strikes to kill the leaders of terrorist organizations in the belief this will hinder or disrupt the group. A research team composed of University of Maryland computer scientists V.S. Subrahmanian, Francesca Spezzano, and Aaron Mannes developed a method of statistical analysis they say can better predict the outcomes of such targeted killings, and potentially avoid situations in which killing one leader leads to the rise of an even more dangerous and brutal one.
The researchers' new method, Shaping Terrorist Organization Network Efficiency (STONE), applies network theory to open source data on terrorist groups to identify various traits of different members, such as their position and influence within the group, and uses these factors to determine who is likely to rise to power should the current leader be killed, as well as how that would effect the groups' disposition. As in "Game of Thrones," a person's rank is a leading determinant in network advancement, the researchers said. Other important traits include influence within the group and connectedness to other members.
Subrahmanian says the research team plans to use their STONE methodology to predict the characters most likely to become the next terror mastermind. The researchers presented their findings in "Reshaping Terrorist Networks," published in the August 2014 issue of Communications of the ACM.
From Defense One
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