Universiteit Leiden

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Research project

Terrorist Group Adaptation & Lessons for Counterterrorism (TERGAP)

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 theory of terrorist group strategic target selection and applying big data analytics and machine learning to test the hypotheses.

Duration
2024 - 2028
Contact
Graig Klein
Funding
European Research Council (ERC) European Research Council (ERC)
Logo European Research Council (ERC)

Terrorist Group Adaptation & Lessons for Counterterrorism (TERGAP) addresses a significant gap in political violence literature by focusing on terrorist groups and improving our understanding of their decision-making. It is widely accepted in the empirical study of political violence, that terrorist groups are rational and strategic actors, but these groups rarely accomplish their political goals and yet continue to use terrorist violence. To understand why terrorism is a persistent problem, we first need to understand how terrorist groups are making strategic decisions and using violence to accomplish their goals.

This creates a fundamental puzzle. We accept terrorist groups as strategic, but we lack a comprehensive understanding of their motivations. One of the basic principles TERGAP explores is that in addition to the political objectives of terrorists, recruiting individuals seeking vengeance or retribution is of central importance to terrorist groups and motivates their strategic target selection.

We must also think about counterterrorism because it influences terrorism strategies and adaptations. But we lack reliable data on counterterrorism. TERGAP aims to build two cross-national data collection efforts that enable big data analytics to identify adaptation patterns. The first dataset focuses on counterterrorism policies and the second dataset, using natural language processing, focuses on counter-terrorist events.

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