Global Terrorism Analysis

An interactive system for visual analysis of global terrorism.

Updated by UN OICT Analytics on November 11, 2016

Project repository

Project Objective

This project provides an Interactive Visual Implementation System (IVIS) of terrorist acts worldwide to help researchers gain a deeper understanding of the patterns of terrorist acts over time around the world. This system aims to identify correlations, clusters, and features of different countries and parties, associated with types of attacks and casualties.

References

Project Team

Center for Data Science - New York University Center for Data Science - New York University

Prof. Greg Watson - New York University
Adjunct Professor Data Science, Center for Data Science
Senior Research Scientist at Oak Ridge National Laboratory

Xianzhi Cao - New York University
Master’s student - Center for Data Science

Caroline Roper - New York University
Master’s student - Center for Data Science