An Application of Natural Language Processing to Classify What Terrorists Say They Want

نویسندگان

چکیده

Knowing what perpetrators want can inform strategies to achieve safe, secure, and sustainable societies. To help advance the body of knowledge in counterterrorism, this research applied natural language processing machine learning techniques a comprehensive database terrorism events. A specially designed empirical topic modeling technique provided machine-aided human decision process glean six categories perpetrator aims from motive text narrative. Subsequently, different models validated aim based on accuracy their association with narrative field, event summary. The ROC-AUC scores classification ranged 86% 93%. Extreme Gradient Boosting model best predictive performance. intelligence community use identified understand incentive structure terrorist groups customize for dealing them.

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ژورنال

عنوان ژورنال: Social sciences

سال: 2022

ISSN: ['2326-988X', '2326-9863']

DOI: https://doi.org/10.3390/socsci11010023