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Machine learning for the automatic identification of terrorist incidents in worldwide news media

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3 Author(s)
Richard Mason ; RAND Corporation, Santa Monica, California, USA ; Brian McInnis ; Siddhartha Dalal

The RAND Database of Worldwide Terrorism Incidents (RDWTI) seeks to index information about all terrorist incidents that occur and are mentioned in worldwide news media, providing a useful resource for policy researchers and decision makers. We examined automated classification methods that could be used to identify news articles about terrorist incidents, thus enabling analysts to read a smaller number of news articles and maintain the database with less effort and cost. The support vector machine (SVM) and Lasso methods were only modestly successful, but a classifier based on the gradient boosting method (GBM) appeared to be very successful, correctly ranking 80% of the relevant articles at the “top of the pile” for examination by a human analyst.

Published in:

Intelligence and Security Informatics (ISI), 2012 IEEE International Conference on

Date of Conference:

11-14 June 2012