Login

Researchers want to predict disasters by mining New York Times archives

The New York Times HQ logo (1020)

Online news has made finding current events easier than ever — but what if it could be used to predict future events as well? Eric Horvitz of Microsoft Research and Kira Radinsky of the Technion-Israel Institute of Technology have built a system that mines over 20 years of New York Times articles for events that could point to other, later developments. In their test model, Horvitz and Radinsky created a system to draw connections between events, then set it loose on the Times database.

The system was able to "learn" correlations between events by looking at sequences of stories in particular places: if an article was published about a drought in one place, for example, there was an 18 percent chance of a drought being reported there later. And both droughts and storms can lead to cholera outbreaks. Not every event (like, say, "cholera outbreak in Rwanda") had enough data to be useful, so it also needed to be able to find and connect patterns from different kinds of events that shared characteristics.

With enough data and a good model, the system could be used to give early warning signs for disasters by mining individual reports and finding larger patterns in them. The general idea of finding ways to predict diseases isn't new, nor is the concept of data mining for prediction, but the wide scope of this project makes it potentially very useful — as long as the system is able to successfully draw correlations between events, and to generalize enough to make them useful, it could be applied to any number of situations.

The Verge
X
Log In Sign Up

forgot?
Log In Sign Up

Forgot password?

We'll email you a reset link.

If you signed up using a 3rd party account like Facebook or Twitter, please login with it instead.

Forgot password?

Try another email?

Almost done,

By becoming a registered user, you are also agreeing to our Terms and confirming that you have read our Privacy Policy.
Spinner.vc97ec6e

Authenticating

Great!

Choose an available username to complete sign up.

In order to provide our users with a better overall experience, we ask for more information from Facebook when using it to login so that we can learn more about our audience and provide you with the best possible experience. We do not store specific user data and the sharing of it is not required to login with Facebook.