corruption

Deep learning methods are used to predict properties of criminal networks.

We have demonstrated how structural properties of criminal networks and machine learning methods can be used to predict links and link features among actors engaged in nefarious activities.

Interact with realistic simulations of corruption networks

Our results show that corruption networks share universal characteristics that are independent of social and cultural differences among countries.