Enhancing patterns with linguistic information for criminal event recognition

Abstract

There are several categories of criminal events. However, one of them is focused on people: criminal events against people. It directly affects some of the guarantee of a person or a family. These events are reported in digital media and, without neglecting, digital news media in Spanish. It is relevant to recognize criminal events against people to get useful information about the public security of citizens. Natural Language Processing has techniques that can be possible their identification. However, fine-grained linguistic analysis is required in order to carry out such task. This paper considers the enhancing the discovered patterns with linguistic information (morphological and POS categories) to recognize criminal events against people from Spanish newspapers. Six categories of criminal events are considered: killing, violation, assault, suicide, kidnapping and sexual exploitation. An experimentation is carried out with a gold standard data set of criminal events. The experimentation shows promising results.