Terrorist Group Adaptation & Lessons for Counterterrorism

Informations projet

TERGAP

N° de convention de subvention: 101116436

DOI

10.3030/101116436

Date de signature de la CE 17 Octobre 2023

Date de début 1 Janvier 2024

Date de fin 31 Decembre 2028

Financé au titre de

• European Research Council (ERC)

Coût total

€ 1 500 000,00

Contribution de l’UE

€ 1 500 000,00

Coordonné par

UNIVERSITEIT LEIDEN
Netherlands

Periodic Reporting for period 1 - TERGAP (Terrorist Group Adaptation & Lessons for Counterterrorism)

Période du rapport: 2024-01-01 au 2026-06-30

Résumé du contexte et des objectifs généraux du projet

Terrorism remains a persistent global security challenge, despite massive financial and political investments in counterterrorism. To understand why terrorism is a persistent problem, we need to understand terrorist groups’ strategic decision-making and violent tactical adaptation that enables their survival.

First, TERGAP examines terrorism as a recruitment and support building tool for manipulating potential supporters’ psychological needs, like vengeance for government repression. TERGAP theorizes that terrorist groups make strategic short-term changes in two violent tactics – (1) attack target selection and (2) attack brutality – following government repression to signal their ability to punish the government and attract support from aggrieved and vengeful individuals. TERGAP proposes a new framework of terrorism as a strategic recruitment tool and tests the expectations using advanced statistical modeling.

Second, central to survival is adapting to changes in counterterrorism, but studying these dynamics is constrained by the current scarcity of counterterrorism datasets. TERGAP resolves this limitation by building two new global datasets: 1) counterterrorism policies, 2) counter-terrorism actions (event-level data). Using these new datasets, TERGAP applies advanced ‘big data’ tools to identify patterns of adaptation. Rather than assuming all terrorist groups respond to counterterrorism in the same way, TERGAP examines how different types of counterterrorism affect different types of groups. This approach emphasizes that there is not a “one-size-fits-all” solution and aims to provide evidence-based strategies that can tailor effective policy responses and enhance security.

TERGAP integrates insights from the social sciences with analytical tools commonly used in the natural and health sciences. This interdisciplinary approach allows the project to detect patterns in complex data that were previously difficult to observe. The creation of two global counterterrorism datasets will significantly improve the quality and scope of quantitative research in the field. These datasets will be publicly available in line with FAIR data principles, enabling researchers worldwide to conduct further robust studies.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

The Counterterrorism Legislation Dataset (CTL) is complete and contains information on legislation changes (new laws, amendments, decrees, and treaties) related to counterterrorism in 111 countries (and territories) from 2010-2020. Introducing CTL addresses one of the biggest limitations in counterterrorism research – a lack of open-access cross-national large-N datasets. Now, researchers can use CTL to analyse motivations for implementing new laws or how counterterrorism legislation influences changes in political violence and terrorist behaviour.

Counterterrorism event data have been collected for sub-Saharan Africa from 2010-2013. The data are not public and will be used in training a machine-coding algorithm.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

TERGAP's use of 'big data' analytics represents a transformative methodological approach to the study of terrorism and counterterrorism. It opens new avenues for studying adaptation, escalation, and survival dynamics not only in terrorism but also in broader conflict processes. TERGAP is designed to reach multiple audiences, including academic researchers, policymakers, security practitioners, and the broader public. There is potential to commercialise a predictive model that analysts can implement prior to advising on counterterrorism or national security actions and policies. The model would help anticipate how targeted groups are likely to respond or react and assess the potential short- and long-term efficacy, efficiency, and effect of different counterterrorism and national security tactics, techniques, procedures, and policies.