Organizational Dynamics Shape Threats and CT Responses
What happens when there are multiple terrorist adversaries at the same time?
The current multi-threat environment makes it hard to assess when to act and whether a specific counterterrorism response will work especially if there isn’t an overt warning sign.
This project aims to study prior terrorist behavior to develop a comprehensive response framework.
This project showcases the role of group-level information and big data in counterterrorism activities. The goals are to develop 1) profiles of key adversarial threats, 2) interactive web-based maps for longitudinal network analysis, and 3) a risk assessment framework to identify potential vulnerabilities and inform CT response efforts. In particular, the research team will continue to expand the “Mapping Militants” open-access website and will use machine learning techniques to help enhance security for the Marine Transportation System (MTS).
This project will use archival information to develop profiles of violent extremist organizations and design an interactive visualization platform to illustrate the relationships among groups. The researchers will also conduct interviews to understand threats to the MTS and inform the development of machine learning algorithms to identify emerging vulnerabilities.
- Martha Crenshaw, Senior fellow at CISAC and FSI and a professor of political science by courtesy (Stanford)
- Iris Malone, Assistant Professor of Political Science and International Affairs (George Washington University)