Public sentiment towards economic sanctions in the Russia–Ukraine war

Abstract

This paper introduces novel data on public sentiment to-wards economic sanctions based on nearly 1 million social media posts in 108 countries during the Russia–Ukraine war by using machine learning. We show the geographi-cal heterogeneity between government stances and public sentiment. Finally, we show how political regimes, trading relationships and political instability can predict how peo-ple perceive this war.