Book chapter · Routledge eBooks · April 22, 2025

Major challenges of searching for crime-related information in a text

Orken J. Mamyrbayev, Nina Khairova, Waldemar Wójcik

Abstract

Research on the prevention of terrorist attacks has increasingly concentrated on analyzing the digital activities of terrorists, particularly their use of the Internet and social media platforms. Numerous studies have also aimed to identify linguistic markers that signal violent extremism, with a specific focus on those associated with “lone-wolf” terrorists. This chapter addresses the challenges associated with defining and identifying crime-related textual information. The analysis conducted emphasizes the potential of information extraction (IE) techniques for effectively extracting crime-related textual information. By applying IE, it is possible to extract key events, entities, and their relationships from texts, which can then be used to construct meaningful inferences about criminal intent, behavior, or patterns. Such approaches enhance the precision of crime detection systems by moving beyond surface-level textual analysis and incorporating deeper semantic and contextual understanding.

Terrorism, Counterterrorism, and Political ViolenceTopic ModelingAdvanced Text Analysis Techniquesinformation extractionterrorist attack preventionlone wolf terrorism

Major challenges of searching for crime-related information in a text

Abstract

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