Higher Order Temporal Analysis of Global Terrorism Data

TL;DR

This paper applies temporal network analysis to the Global Terrorism Database to uncover the evolving patterns and properties of terrorism activities over time, aiding security efforts.

Contribution

It introduces a graph-based methodology for analyzing the temporal evolution of global terrorism data, providing insights into its dynamics.

Findings

Identified key temporal patterns in terrorism activities.

Revealed evolving network structures of terrorist incidents.

Enhanced understanding of terrorism dynamics over time.

Abstract

Temporal networks are a fundamental and flexible way of describing the activities, relationships, and evolution of any complex system. Global terrorism is one of the biggest concerns of recent times. It is also an example of a temporal network that evolves over time. Graph analytics can be used to explore salient properties of the terrorism network to understand its modus operandi, which can be used by the global alliance of security and government entities to form a co-ordinated response to this threat. We present graph based analysis to understand temporal evolution of global terrorism using the Global Terrorism Database (GTD).