Creating a Knowledge Base for Interventions Countering (Violent) Extremism: Intervention Goals and Mechanisms for Different Ideologies.


  • Helma van den Berg TNO (Netherlands Organisation for Applied Scientific Research), the Netherlands
  • Dianne A. van Hemert TNO (Netherlands Organisation for Applied Scientific Research), the Netherlands
  • Anthony J. van Vliet TNO (Netherlands Organisation for Applied Scientific Research), the Netherlands


Knowledge Base, CVE Interventions, Radicalization, Intervention Goals, Ideologies


Many interventions aim to tackle violent radicalization. Monitoring the implementation of interventions results in a better identification of effective interventions and in a more appropriate selection of applicable interventions for practitioners. Using meta-analytic and network analytic methods, we present a method to store and retrieve information about countering (violent) extremism (CVE) interventions using a knowledge base that allows for different searches for relevant information. We describe the construal of this knowledge base using data on 99 European CVE interventions. Subsequently, we present inferences that can be drawn from this sample. Key determinants to identify whether radicalizing people are eligible for participating in CVE interventions were found to be friendship relations, group affiliation and available intelligence. Dependent on the ideology targeted by the CVE intervention different goals and mechanisms were identified. Information on financial costs of CVE interventions was often not available in open sources. Implications of representing the information on CVE interventions into a knowledge base are discussed.

Author Biography

Helma van den Berg, TNO (Netherlands Organisation for Applied Scientific Research), the Netherlands

This research was made possible by a FP7 European Union research grant (nr. 312235) as part of a larger research project named IMPACT Europe (Innovative Method and Procedure to Assess Counter-violent radicalisation Techniques), including twelve partner organizations across Europe (see Correspondence regarding this article should be addressed to Helma van den Berg (, TNO, Defence, Safety and Security, Kampweg 55, 3769 DE, Soesterberg, the Netherlands.


Ballou M. (1995). Psychological Interventions: A guide to Strategies. Praeger Publishers/Greenwood Publishing Group, Inc: Westport, CT, USA.

Bhui, K. S., Hicks, M. H., Lashley, M., & Jones, E. (2012). A public health approach to understanding and preventing violent radicalisation. BMC medicine, 10(1), 16.

Bowie, N. G. (2017). Terrorism Events Data: An Inventory of Databases and Data Sets, 1968-2017. Perspectives on Terrorism, 11(4).

Bossong, R. (2014). EU cooperation on terrorism prevention and violent radicalisation: frustrated ambitions or new forms of EU security governance? Cambridge Review of International Affairs, 27(1), 66-82.

Carley, K.M., & Kamneva, N.Y. (2004). A Network Optimization Approach for Improving Organizational Design. Carnegie Mellon University, School of Computer Science, Institute for Software Research International, Technical Report CMU-ISRI-04-102.

Cooper, H., Hedges, L. V., Valentine, J. C. (Eds.). (2009). The Handbook of Research Synthesis and Meta-Analysis, Second Edition. New York: Russell Sage.

Cramer, A.O.J., Waldorp, L.J., van der Maas, H.L.J., & Borsboom. D. (2010). Comorbidity: a network perspective. Behavioral and Brain Sciences, 33(2-3), 137-150.

Dalege, J., Borsboom, D., van Harreveld, F., van den Berg, H., Conner, M., & van der Maas, H. L. (2016). Toward a formalized account of attitudes: The Causal Attitude Network (CAN) model. Psychological review, 123(1), 2.

Dalege, J., Borsboom, D., van Harreveld, F., & van der Maas, H. L. (2017). Network analysis on attitudes: A brief tutorial. Social psychological and personality science, 8(5), 528-537.

Doosje, B., Moghaddam, F. M., Kruglanski, A. W., de Wolf, A., Mann, L., & Feddes, A. R. (2016). Terrorism, radicalisation and de-radicalisation. Current Opinion in Psychology, 11, 79-84.

Epskamp, S., Cramer, A.O.J., Waldorp, L. J., Schmittmann, V. D., & Borsboom, D. (2012). Qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48(4), 1-18.

Feddes, A. R., & Gallucci, M. (2015). A literature review on methodology used in evaluating effects of preventive and de-radicalisation interventions. Journal for Deradicalisation, 5(4), 1-27.

Fruchterman, T. M., & Reingold, E. M. (1991). Graph drawing by force‐directed placement. Software: Practice and experience, 21(11), 1129-1164.

Gielen, A. J. (2017). Countering Violent Extremism: A Realist Review for Assessing What Works, for Whom, in What Circumstances, and How? Terrorism and Political Violence, 1-19.

Horgan, J. (2009). Walking away from terrorism: Accounts of disengagement from radical and extremist movements. Routledge, New York.

Hunter, J.E., & Schmidt, F.L. (2004). Methods of Meta-Analysis: Correcting Error and Bias in Research Findings. Thousand Oaks, CA: Sage.

Ioannidis, J. P., Greenland, S., Hlatky, M. A., Khoury, M. J., Macleod, M. R., Moher, D., & Tibshirani, R. (2014). Increasing value and reducing waste in research design, conduct, and analysis. The Lancet, 383, 166-175.

Johnson, D. H., & Sabourin, M. E. (2001). Universally accessible databases in the advancement of knowledge from psychological research. International Journal of Psychology, 36(3), 212-220.

Koehler, D. (2016). Understanding Deradicalisation: Methods, Tools and Programs for Countering Violent Extremism. London, Taylor & Francis.

Koehler, D. (2014). German Right-Wing Terrorism in Historical Perspective. A First Quantitative Overview of the ‘Database on Terrorism in Germany (Right-Wing Extremism)’–DTGrwx’Project. Perspectives on terrorism, 8(5).

Krackhart, D., & Carley, K.M. (1998). A PCANS model of structure in organizations. In: International Symposium on Command and Control Research and Technology, Monterey, CA.

Munafò, M. R., Nosek, B. A., Bishop, D. V., Button, K. S., Chambers, C. D., du Sert, N. P., …& Ioannidis, J. P. (2017). A manifesto for reproducible science. Nature Human Behaviour, 1, 0021.

Mook, D. G. (2001). Psychological research: The ideas behind the methods. London: Norton.

Ritchey, T. (2011a) Wicked Problems – Social Messes: Decision support Modelling with Morphological Analysis. Berlin: Springer.

Ritchey, T. (2011b). Decision Support Modelling with Morphological Analysis Series: Risk, Governance and Society, 17. Springer Science & Business Media.

Schuurman, B. (2018). Research on Terrorism, 2007–2016: A Review of Data, Methods, and Authorship. Terrorism and Political Violence, DOI: 10.1080/09546553.2018.1439023.

Yardley, L., Morrison, L., Bradbury, K., & Muller, I. (2015). The person-based approach to intervention development: application to digital health-related behavior change interventions. Journal of medical internet research, 17(1).