Social networks play a critical role in the formation of criminal and radical groups. However, understanding of these formations relies on difficult to collect data. We present an approach where narrative data from the trial of the 1995 Paris Metro and RER bombings was used to extract actors, places, groups and actions that led to the formation of the radical group. This data was dynamically visualized and allowed one to follow the process of terrorist group formation. An important part of the approach is the inclusion of the individuals who were parts of the social network of the radicalized individuals but who did not get radicalized (e.g. members of a soccer team). We emphasize the importance of the Natural Language Processing (NLP) in timely information extraction followed by dynamic visualization.
Bobashev G., Sageman M., Evans A.L., Wittenborn J., Chew R.F.. (2018). Turning Narrative Descriptions of Individual Behavior into Network Visualization and Analysis: Example of Terrorist Group Dynamics. International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation