Abstract
In many real-world contexts, there is a pressing need to automatically screen for potential perpetrators, such as school shooters, whose prevalence in the population is extremely low. We first explain one possible obstacle in addressing this challenge, which is the confusion between “recognition” and “localization” during a search process. Next, we present a pragmatic screening methodology to the problem along Jaynes Bayesian hypothesis testing procedure. According to this approach, we should first focus our efforts on reducing the size of the haystack rather than on the identification of the needle. The third and major methodological contribution of the paper is in proposing that we may reduce the size of the haystack through the identification and use of unique data cues we describe as “impostors’ cues”. An experiment performed on an artificial data set of 7000 texts, shows that when incorporating these cues in the hypothesis testing procedure, they significantly improve the automatic screening of objects characterized by an attribute of a low prevalence (i.e. a psychopathic signature). The relevance of the proposed approach for Big Data and Homeland security is explained and discussed.
Highlights
In many real-world contexts, there is a pressing need to automatically screen for potential perpetrators, such as school shooters, whose prevalence in the population is extremely low
When screening for the perpetrators through Jaynes Bayesian hypothesis testing procedure, and given the low prevalence of the target group, it is almost inevitable that the data we collect work “negatively” from a strong negative e score to a less negative e score
Our second claim is that while Jaynes hypothesis testing procedure cannot provide us with the smoking gun for identifying the perpetrator, it clearly provides us with a way of reducing the size of the haystack in which we are searching
Summary
In many real-world contexts, there is a pressing need to automatically screen for potential perpetrators, such as school shooters, whose prevalence in the population is extremely low. If we adopt the Shannon’s idea of entropy the most important challenge facing us in identifying/locating a lone wolf, is the formation of the appropriate questions/features that will lead us to the localization/recognition of the perpetrator.
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