Terrorism incidents and characteristics, a multilevel latent class model

Luciano Nieddu; Roberta Varriale

doi:10.71014/sieds.v80i4.430

Authors

Luciano Nieddu UNINT University
Roberta Varriale Sapienza University of Rome

DOI:

https://doi.org/10.71014/sieds.v80i4.430

Abstract

The aim of this study is to explore the impact of the 2001 attacks on the World Trade Center on the characteristics of terrorism worldwide and in individual countries using information from the Global Terrorism Database (GTD), a longitudinal dataset that provides detailed data on terrorist events worldwide. We focus on terrorist activity within a country, organizing the data by attacks and countries to detect latent patterns. We restrict our attention on a limited period of time, namely 7 years, and apply a multilevel latent class model that enables for simultaneous clustering of attacks and events into groups exhibiting distinctive profiles based on observed terrorism-related variables.

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