Publication:
LEVERAGING BIG DATA AND MACHINE LEARNING TO IDENTIFY AND FORECAST FACTORS THAT INFLUENCE THE WAR IN UKRAINE

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Authors
Polzin, Benjamin
Subjects
big data
ML
machine learning
GDELT
Global Database of Events Language and Tone
Advisors
Yoshida, Ruriko
Schuchard, Ross J.
Date of Issue
2023-06
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
Military analysts often rely on publicly available information from traditional news platforms and social media to gain insight on the development of international events of interest. Relying too heavily on English language sources can be detrimental to the quality of analysis, however, particularly if focusing on non-Western actors. Examining the ongoing war between Russia and Ukraine, it is hard to quickly aggregate publicly available information in Ukrainian, Russian, Persian, and other non-English languages.The Global Database of Events, Language, and Tone (GDELT) offers a potential solution, as it monitors the world’s news media in over 100 languages from every country in the world, with 65 languages being automatically translated into English. While the GDELT data collection is openly available, its size and complexity present a significant challenge in collecting, parsing, and scrubbing relevant data.This study aims to leverage the GDELT dataset to forecast important factors and actors influencing the war in Ukraine and will use extracted data and machine learning techniques to develop predictive models.
Type
Thesis
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Series/Report No
Department
Operations Research (OR)
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Distribution Statement
Approved for public release. Distribution is unlimited.
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Copyright is reserved by the copyright owner.
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