Crime / Law

Can you predict the next Bin Laden?

In sort of the same way you can predict what happens next on Game of Thrones, applied statistics. A research team from the University of Maryland has devised a system to predict the top three players (out of hundreds) most likely to become the new leader of a given terror group when you remove the person in charge. The method also predicts whether the terror group will become more dangerous after the succession or less so and how the terror network will evolve as a result.
University of Maryland computer scientists V.S. Subrahmanian, Francesca Spezzano, and Aaron Mannes call their method Shaping Terrorist Organization Network Efficiency or STONE. They published their findings in the August 2014 issue of Communications of the ACM.
Using carefully cultivated open-source data on four terrorist networks, al-Qaeda, Hamas, Hezbollah, and Lashkar-e-Taiba (the group associated with the 2008 terror attacks in Mumbai), they looked to explain how the removal of specific individuals would change the group in order to predict who would rise in the organization if that leader was removed. Some of the variables include the role that the leader plays, such as fundraiser, spiritual leader or recruiter; how dangerous he was on the basis of hostility and capability; and the potential for retaliation in the event that he was taken out.
This application of statistical weights and measures to group dynamics is called network theory. It’s the sort of analysis that the Facebook Data Science team is constantly undertaking to see how people influence one another on the site, such as which of your friends can influence whether you like specific products and brands.

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