Spatiotemporal analysis of nontraditional security issues evolution globally: evidence from news big data

Area of Science:

• Global Security Studies
• International Relations
• Data Science

Background:

• Non-traditional security (NTS) challenges have escalated globally since the 21st century.
• Existing research often lacks a comprehensive, data-driven global perspective on NTS evolution.

Purpose of the Study:

• To analyze the spatiotemporal evolution of global non-traditional security (NTS) issues from 2000 to 2023.
• To quantify the frequency and impact of NTS activities using novel indicators.
• To identify distinct phases and evolving patterns of NTS challenges worldwide.

Main Methods:

• Utilized event data from the Global Database of Events, Language, and Tone (GDELT).
• Constructed a global panel dataset for 153 countries (2000-2023).
• Developed and applied the CEN (count event number) and NSII (NTS impact index) indicators to measure NTS scale and severity.

Main Results:

• Identified five distinct phases in global NTS evolution, with peaks in 2012 and 2016.
• Peaks were primarily driven by terrorism and social instability in the Middle East, South Asia, and Africa.
• Observed a shift in NTS hotspots towards more dispersed and transregional patterns, indicating risk diffusion.

Conclusions:

• NTS risks are increasingly interconnected and transregional, necessitating adaptive, cross-border governance.
• Continuous monitoring mechanisms are crucial for effective policy responses to evolving NTS threats.
• The study provides a data-driven framework for tracking and understanding global NTS dynamics.