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Why a 12-year-old forecasting paper has stood the test of time

A 12-year-old Amazon forecasting paper just won KDD's test-of-time award. Here's why ML models predicting civil unrest still matter.

Reporting by Amazon Science 1 min brief
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The KeyNews take

Why it matters

Amazon Scholar's decade-old machine learning work on predictive forecasting has proven durable enough to win institutional recognition, signaling that foundational ML research on real-world prediction problems maintains long-term value and relevance to enterprise AI applications.

The key facts

9 to know

  1. 2014 paper on forecasting civil unrest in Latin America

  2. Coauthored by Amazon Scholar Aravind Srinivasan

  3. Won test-of-time award at KDD 2025

  4. 12-year research durability benchmark

  5. Focus on predictive modeling for geopolitical events

  6. Paper published 2014, won test-of-time award at KDD 2025

  7. Coauthor: Aravind Srinivasan, Amazon Scholar

  8. Focus: Forecasting civil unrest in Latin America using machine learning

  9. Venue: KDD (Knowledge Discovery and Data Mining) conference

Go to the source

Amazon Scienceamazon.science

Publisher excerpt: Amazon Scholar Aravind Srinivasan coauthored a 2014 paper about forecasting civil unrest in Latin America, which won a test-of-time award at KDD 2025.
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