Title

Reading Between the Lines: Prediction of Political Violence Using Newspaper Text

Author(s)

Hannes Mueller Hannes Mueller (Institut d’Analisi Econòmica (IAE-CSIC), Barcelona GSE,)

Christopher Rauh Christopher Rauh (University of Cambridge)

Abstract

This article provides a new methodology to predict conflict by using newspaper text. Through machine learning, vast quantities of newspaper text are reduced to interpretable topic shares. We use changes in topic shares to predict conflict one and two years before it occurs. In our predictions we distinguish between predicting the likelihood of conflict across countries and the timing of conflict within each country. Most factors identified by the literature, though performing well at predicting the location of conflict, add little to the prediction of timing. We show that news topics indeed can predict the timing of conflict onset. We also use the estimated topic shares to document how reporting changes before conflict breaks out.

Creation Date

2016-06

Section URL ID

Paper Number

2

URL

https://esoc.princeton.edu/publications/esoc-working-paper-2-reading-between-lines-prediction-political-violence-using

File Function

Jel

D74, Z18, F51

Keyword(s)

Violence, Public Opinion

Suppress

false

Series

12