Descripción del proyecto
Una nueva forma de reforzar la lucha antiterrorista
Los grupos terroristas se adaptan continuamente a los cambios, manteniendo su relevancia y poder a pesar de los esfuerzos antiterroristas. Esta capacidad de adaptación supone un reto importante para la seguridad mundial, ya que las estrategias tradicionales a menudo tienen dificultades para seguir el ritmo de la evolución de sus tácticas e ideologías. En este contexto, el equipo del proyecto TERGAP, financiado por el Consejo Europeo de Investigación, elaborará un marco teórico detallado y utilizará métodos cuantitativos. En el proyecto, que integra investigaciones sobre psicología política, movimientos sociales y terrorismo, se utiliza análisis de datos masivos y aprendizaje automático para identificar pautas de adaptación. El equipo del proyecto considera el terrorismo como una herramienta de reclutamiento, que aprovecha las necesidades psicológicas como la venganza. En TERGAP se pondrán a prueba los cambios estratégicos a corto plazo tras la represión gubernamental utilizando el análisis de coincidencias de eventos. También se recopilarán datos sobre las políticas y acciones antiterroristas a nivel mundial.
Objetivo
Terrorist groups find ways to adapt to changes in their environment to stay relevant and powerful. This project offers new insights into this phenomenon by developing a more nuanced theoretical strategic framework and using quantitative methods to examine how terrorist groups survive, and sometimes thrive, despite efforts to combat them. This is accomplished by integrating political psychology, social movement, and terrorism research, and applying big data analytics and machine learning common in brain sciences, natural sciences, and bioinformatics to identify adaptation patterns in terrorist attack target selection and brutality.
First, this project frames terrorism as a recruitment tool for manipulating potential supporters’ psychological needs, like vengeance. Repressive government actions lead to desires for vengeance and thus create opportunities for acts of terrorism specifically attacking the repressive actor to signal a terrorist group’s capability for fulfilling this psychological need. As such, we should observe strategic short-term changes in terrorism following government repression in the data. This is tested using Event Coincidence Analysis, a method for identifying synchronization patterns and trigger rates from one event to another.
Second, because terrorist groups can also adapt to changes in counterterrorism, this project proposes two data collection efforts that enable big data analytics to identify adaptation patterns. The first focuses on counterterrorism policies using government reports and covers a global sample of countries. The second creates a novel large-N cross-national counter-terrorist actions dataset using natural language processing machine coding of news articles. Hierarchical clustering analyses will then be used to detect patterns of terrorist group adaptive behaviours and build predictive models that anticipate adaptation. This has implications to improve counterterrorism and make it more proactive, focused, and effective.
Ámbito científico
- social sciencespolitical sciencespolitical transitionsterrorism
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencescomputer and information sciencesdata sciencenatural language processing
- social sciencespolitical sciencespolitical transitionsarmed conflicts
- social sciencespolitical sciencespolitical transitionsrevolutions
Palabras clave
Programa(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Régimen de financiación
HORIZON-ERC - HORIZON ERC GrantsInstitución de acogida
2311 EZ Leiden
Países Bajos