Seeing the Future: Predicting Irregular Leadership Changes

Our new article “Crystal Cube: Forecasting Disruptive Events” is now available, gold open access, in Applied Artificial Intelligence. Here’s the abstract:

Disruptive events within a country can have global repercussions, creating a need for the anticipation and planning of these events. Crystal Cube (CC) is a novel approach to forecasting disruptive political events at least one month into the future. The system uses a recurrent neural network and a novel measure of event similarity between past and current events. We also introduce the innovative Thermometer of Irregular Leadership Change (ILC). We present an evaluation of CC in predicting ILC for 167 countries and show promising results in forecasting events one to twelve months in advance. We compare CC results with results using a random forest as well as previous work.

Read the full article on the Applied Artificial Intelligence/Taylor & Francis website.

This is a continuation of our previous work in predicting disruptive events. If you want to play with it, you can see our most recent predictions live on the Crystal Cub website hosted by JHU/APL.