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Statistical modelling of a terrorist network
Author(s) -
Aitkin Murray,
Vu Duy,
Francis Brian
Publication year - 2017
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/rssa.12233
Subject(s) - terrorism , hierarchy , computer science , latent class model , statistical model , statistical analysis , network model , bayesian network , group (periodic table) , class (philosophy) , bayesian probability , computer security , criminology , artificial intelligence , psychology , machine learning , statistics , mathematics , political science , law , chemistry , organic chemistry
Summary The paper investigates the group structure in a terrorist network through the latent class model and a Bayesian model comparison method for the number of latent classes. The analysis of the terrorist network is sensitive to the model specification. Under one model it clearly identifies a group containing the leaders and organizers, and the group structure suggests a hierarchy of leaders, trainers and ‘foot soldiers’ who carry out the attacks.