The National Science Foundation (NSF) awarded a $300,000 Project Grant under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program to the University of Alabama to extend and further develop the Correlates of War Militarized Interstate Dispute (COWMID) dataset. This 3-year project aims to improve the accuracy and consistency of the COWMID dataset, which provides infrastructure for studying the onset and escalation of international conflicts. The researchers will use supervised machine learning models to identify and classify militarized interstate events from newspaper articles, reducing the costs of data collection and enabling near real-time availability of conflict data for policymakers and researchers. The project involves hand-coding a portion of the newspaper articles as well to train and validate the machine learning models. No subawards are planned for this grant.
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