TERGAP
Financiado
Terrorist Group Adaptation & Lessons for Counterterrorism
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 quanti...
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.
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Duración del proyecto: 59 meses
Fecha Inicio: 2024-01-01
Fecha Fin: 2028-12-31
Fecha Fin: 2028-12-31
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-01-01
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
ERC-2023-STG:
ERC STARTING GRANTS
Cerrada
hace 2 años
Presupuesto
El presupuesto total del proyecto asciende a
2M€
Líder del proyecto
UNIVERSITEIT LEIDEN
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5