When conducting an investigation into a criminal network, data on social and criminal relationships between people should play a leading role, and not suppositions. This is one of the recommendations made by Paul Duijn based on his criminological study. He will be awarded a PhD by the University of Amsterdam for his research on Thursday 22 December.
Currently, police detectives usually form an impression of a criminal network based on their own self-chosen criteria. These criteria relate to such things as the presence of a hierarchical structure or achieving a turnover of at least a few hundred thousand euros in criminal profits. However, Duijn’s research shows that selection based on criteria only provides a restricted and skewed impression of reality.
In order to gain a better impression of criminal structures, Duijn combined various types of information on the relationships between 22,000 known criminals. This concerned information from informers found in arrest reports, and information from police reports and social media. ‘Each type of information provides its own perspective on relationships between these actors. By combining these layers and testing them against one another, an impression is formed of the structure of such a criminal network which is as objective and complete as possible.’
The 22,000 potential criminals in the data set were involved in various types of criminality at an international level, such as the production of synthetic drugs, cannabis farming, extortion and money laundering. The factor they had in common was their relationship to a specific geographical area, used as a pragmatic yet arbitrary boundary for the data set.
When basing himself on a social network analysis, the PhD candidate saw little of the supposed hierarchy within criminal networks in the network structure and dynamics. ‘The relationships are more fluid and opportunistic in such a criminal network. Although there are figureheads or people with more say, the classical view of a Mafia boss running an entire network via a number of trusted henchmen is too simplistic. The network operates as a complex adaptive system, which is constantly adapting to changing circumstances, and where no-one can have a complete overview of the activities and entire structure.’
Duijn unleashed a number of algorithms on his network model to determine possible effects of various police interventions. This established that dealing with the criminals in managing roles is not the most effective way to take down a network. ‘It is tempting to take on the leading figures, the Holleeders so to speak, because they have many offences to answer for. But that reflects thinking at the micro-level, while our models show that a systematic approach is more effective in the long term.’
Such a systematic approach takes the complexity and interwoven nature of the network into account. Duijn’s simulation shows that the arrested leaders are quickly replaced without any harm being done to the network. Certain specialists, such as lab technicians in the synthetic drugs trade or notaries public in the money laundering business are much more essential in continuing criminal activities. ‘Although they too are initially replaced, if you continue to direct your detective work towards such key positions in the long term and also arrest the replacements of the replacements, the pool of specialists will eventually dry up. Such a network will then really begin to experience problems.’ However, Duijn emphasises that such an approach requires time, perseverance and closely fine-tuning information acquisition, preventive measures and investigative activities. ‘When removing such a specialist and after this has been done, you need to closely monitor the network even more carefully to discover who his successor is. That is ultimately the way to achieve the best results in combating organised crime.’
Mr P.A.C. Duijn: Detecting and Disrupting Criminal Networks. A Data Driven Approach. Supervisors: Professor A.G. Hoekstra and Professor Z.J.M.H. Geradts
The doctoral thesis defence ceremony will take place on Thursday 22 December, at 12:00. Venue: Agnietenkapel, Oudezijds Voorburgwal 231, Amsterdam.