Could language analysis tools detect lone wolf terrorists before they act?

Nidal Hasan, the US army psychiatrist turned lone wolf terrorist By Alex Fradera By the time a terrorist attack has begun, the security services have already failed. But the challenge they face in detecting potential attacks is substantial, especially since the tactic of terrorism has increasingly been taken up by individual attackers inspired by, but not directly beholden to, formal movements. Spotting a lone wolf among the flock is no easy task, especially when it relies on a bottleneck of human analysis. A new paper in the journal Aggression and Violent Behavior uses a test case of a real lone wolf attack to explore ways we may be able to deal with this in the future. Using online language analysis tools, it hunts within blocks of text for the warning signs we might otherwise miss, with the hope of helping us to more effectively detect the predator. Giti Zahedzadeh of the Centre for Neuroeconomic Studies at Claremont Graduate University in California wanted to see what insights could be gleaned about violent tendencies by analysing text using the open-source web application Voyant. The application has a number of features such as creating word clouds, word frequency lists, and word association chains to pull out patterns from blocks of text. The raw data Zahedzadeh used were writings by Nidal Hasan, the US military psychiatrist who turned traitor and went on an ideologically motivated mass shooting in 2009 in Fort Hood, Texas, killing 13 and injuring many more. Hasan, wh...
Source: BPS RESEARCH DIGEST - Category: Psychiatry & Psychology Authors: Tags: Language Technology Terrorism Source Type: blogs