Machine Learning for Peace: tracking civic spaces around the globe

Civic spaces can serve as a barometer of political health. Policymakers and researchers need accurate analysis of the civic spaces around the globe in order to know what locations need help. Devlab@Duke has launched a new interactive online tool to address shrinking civic space and growing authoritarianism around the world. This tool will put incredibly fine-grained data and highly accurate forecasts of civic space events into the hands of policymakers, practitioners, and researchers working to defend democracy.

This event debuted The Machine Learning for Peace (MLP) project, which combines recent advances in natural language processing, recurrent massive web scraping of more than 100 international, regional, and local sources of online news, high-frequency economic data, and machine learning forecasting models to produce cutting-edge research that can guide policy and practice. Each month, we scrape thousands of new articles from these sources to add to this enormous corpus of digital news. Each article is classified according to 19 events that capture changing civic space events and 22 events that capture the efforts of authoritarian regimes to influence developing countries. To date, MLP has scraped and processed more than 68 million news articles across more than 20 languages and 30 countries. The launch event took place on December 15, 2021.
mlp.trinity.duke.edu