We develop a framework that uses Web content to obtain quantitative information about a phenomenon that would otherwise require the operation of large scale, expensive intelligence exercises. Exploiting indexed reliable sources such as online newspapers and blogs, we use unambiguous query terms to characterize a complex evolving phenomena and solve a security policy problem: identifying the areas of operation and modus operandi of criminal organizations, in particular, Mexican drug tracking organizations over the last two decades. We validate our methodology by comparing information that is known with certainty with the one we extracted using our framework.We show that our framework is able to use information available on the web to eciently extract implicit knowledge about criminal organizations. In the scenario of Mexican drug tracking, our ndings provide evidence that criminal organizations are more strategic and operate in more dierentiated ways than current academic literature thought.

Knowing where and how criminal organizations operate using web content

Coscia M;
2012

Abstract

We develop a framework that uses Web content to obtain quantitative information about a phenomenon that would otherwise require the operation of large scale, expensive intelligence exercises. Exploiting indexed reliable sources such as online newspapers and blogs, we use unambiguous query terms to characterize a complex evolving phenomena and solve a security policy problem: identifying the areas of operation and modus operandi of criminal organizations, in particular, Mexican drug tracking organizations over the last two decades. We validate our methodology by comparing information that is known with certainty with the one we extracted using our framework.We show that our framework is able to use information available on the web to eciently extract implicit knowledge about criminal organizations. In the scenario of Mexican drug tracking, our ndings provide evidence that criminal organizations are more strategic and operate in more dierentiated ways than current academic literature thought.
2012
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-1-4503-1156-4
Query
Data retrieval
Knowledge discovery process
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/261017
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