Using Information Cascades to Fight Terrorism
http://techcrunch.com/2015/09/27/researchers-from-arizona-state-university-take-the-war-online-back-to-isis/
http://www.nytimes.com/2015/06/13/world/middleeast/isis-is-winning-message-war-us-concludes.html?_r=0
http://phys.org/news/2015-07-countering-social-persuasion-extremist-groups.html
Over the past several years, the war on terror has become increasingly more digital in nature. This change has proven difficult for the U.S. and other governments. In fact, in June, the New York Times reported that a leaked U.S. State Department document from an internal memo discussed how, thus far, ISIS has outmaneuvered several of the world’s most technologically advanced nations as they attempt to derail the organizations online operations, specifically recruitment.
In order to address this threat, the analysis of information cascades is being put to use. Information cascades can strongly influence the actions of a significant number of individuals as a result of the decisions made by a few people or potentially the influence of a single person. These cascades are the result of an individual ignoring original information that they possessed and they instead make decisions based on the actions of previous individuals. As such, terror groups are heavily using social media to encourage people to take up their cause, relying on information cascades to help them spread their message.
The CyberSocio Intelligent-Systems Laboratory group at Arizona State University is currently examining how one can determine whether a piece of information will go viral. In short, they analyze the qualities of the information. The idea is that one day they may be able to accurately predict which terrorist messages will gain traction online, and thus they can intervene and prevent the spread of that message, precisely attacking the recruitment efforts of terror groups. By gaining an understanding of the message characteristics and social issues involved that are more likely to be found appealing in online communities, the group hopes to develop algorithms capable of deducing which posts will eventually gain traction, helping to greatly hinder the recruitment efforts of these organizations using the ideas behind their own recruitment process.