Machine Learning for Peace

  • Villamizar Chaparro, Santiago Mateo (CoI)
  • Wibbels, Erik (PI)
  • Springman, Jeremy (CoPI)
  • Adiguzel, Serkant (CoI)
  • Romero, Diego (CoI)
  • Lin, Zung-Ru (CoI)
  • Su, Hanling (CoI)
  • Moratz, Donald (CoI)
  • Gansey, Rethis Togbedji (CoI)
  • Swami, Jitender (CoI)
  • Soltani, Mahda (CoI)

Project: Research

Project Details

Description

Machine Learning for Peace (MLP) harnesses the power of machine learning and data analytics to enhance democracy promotion and crisis response efforts worldwide. MLP’s digital tools provide fine-grained data tracking and forecasting major political events across more than 60 countries by continuously scraping and processing tens of millions of articles published by more than 300 local, regional, and international news sources in nearly 40 languages. This infrastructure provides up-to-date data on recent and historical trends in civic space and foreign influence and builds forecasting models that learn from historical patterns to predict how conditions are likely to change in the near future.
AcronymML4P
StatusActive
Effective start/end date1/08/20 → …

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.