Multinational military exercises (MMEs), commonly referred to as war games, are cooperative, non-combative actions undertaken bythe militaries of multiple states intended to improve future military cooperation.
In this research we identify three types of exercises: warfighting, humanitarian, and peacekeeping. We then ask two research questions:
(1) How can we use machine learning to to classify news articles into the three MME types?
(2) What can we learn about international relations from exploring MMEs over the 1980-2010 time period?
To answer these questions, we structured and labeled a database of MMEs and the news stories describing them. We then used supervised machine learning to classify stories, achieving accuracies from 88 to 93.6%, and show that the multilayer perceptron outperforms the support vector machine algorithm.
Workflow Structure:
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Models Confusion Matrix: