Identifying geopolitical event precursors using attention-based LSTMs.

ABSTRACT: Forecasting societal events such as civil unrest, mass protests, and violent conflicts is a challenging problem with several important real-world applications in planning and policy making. While traditional forecasting approaches have typically relied on historical time series for generating such forecasts, recent research has focused on using open source surrogate data for more accurate and timely forecasts. Furthermore, leveraging such data can also help to identify precursors of those events that can be used to gain insights into the generated forecasts. The key challenge is to develop a unified framework for forecasting and precursor identification that can deal with missing historical data. Other challenges include sufficient flexibility in handling different types of events and prov

SUBMITTER: Hossain KSMT 

PROVIDER: S-EPMC9662789 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature