Commissioned by WODC (Research and Documentation Centre of the Ministry of Justice and Security), CentERdata conducts research on the indicators of (organized) crime and subversion in industrial areas. The objective of the study is to determine the state of an industrial area concerning the occurrence and development of (organized) crime and subversion. Put differently: which indicators can predict where an industrial area finds itself on a ‘sliding scale’ of crime and subversion? By disentangling indicators and patterns of (organized) crime and subversion, we can develop a method with which public authorities and policy makers can judge the level of criminal and subversive activities taking place in a certain area and develop appropriate (preventive) policy measures.
To arrive at the best predictors, we first make use of existing knowledge and insights from other research and from the field. Phase 1 of this project was a preliminary research in which a literature review was conducted and possible indicators and data sources were discussed during an expert meeting and interviews. This resulted in a conceptual model and a short list with a ranking of potential indicators of crime and subversion. In phase 2, suitable data will be collected from a wide range of sources. Subsequently, advanced Data Science techniques, such as Natural Language Processing and Machine Learning, will be applied to determine which indicators are the best predictors for the stage at which an industrial area finds itself on a ‘sliding scale’ of (organized) crime and subversion.
This project is carried out in cooperation with the Expertisecentrum Veiligheid (Center of Expertise on Security) of Avans University of Applied Sciences and the Data Science Center (DSC/t) of Tilburg University.