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)

Proyecto: Investigación

Detalles del proyecto

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.
SiglaML4P
EstadoActivo
Fecha de inicio/Fecha fin1/08/20 → …

Huella digital

Explore los temas de investigación que se abordan en este proyecto. Estas etiquetas se generan con base en las adjudicaciones/concesiones subyacentes. Juntos, forma una huella digital única.