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Geometric persistence and distributional trends in worldwide terrorism.

Authors :
James, Nick
Menzies, Max
Chok, James
Milner, Aaron
Milner, Cas
Source :
Chaos, Solitons & Fractals. Apr2023, Vol. 169, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

This paper introduces new methods for studying the prevalence of terrorism around the world and over time. Our analysis treats spatial prevalence of terrorism, the changing profile of groups carrying out the acts of terrorism, and trends in how many attacks take place over time. First, we use a time-evolving cluster analysis to show that the geographic distribution of regions of high terrorist activity remains relatively consistent over time. Secondly, we use new metrics, inspired by geometry and probability, to track changes in the distributions of which groups are performing the terrorism. We identify times at which this distribution changes significantly and countries where the time-varying breakdown is most and least homogeneous. We observe startling geographic patterns, with the greatest heterogeneity from Africa. Finally, we use a new implementation of distances between distributions to group countries according to their incidence profiles over time. This analysis can aid in highlighting structural similarities in outbreaks of extreme behavior and the most and least significant public policies in minimizing a country's terrorism. • Two decades of events from the Global Terrorism Database are studied. • Time-varying cluster analysis shows substantial geographic persistence of attacks. • Metrics from geometry and probability study compositional changes in perpetrators. • Time series analysis investigates trends in terrorism intensity over time. • Significant geographical patterns are revealed, particularly between Asia and Africa. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09600779
Volume :
169
Database :
Academic Search Index
Journal :
Chaos, Solitons & Fractals
Publication Type :
Periodical
Accession number :
162540871
Full Text :
https://doi.org/10.1016/j.chaos.2023.113277