Twitter and Crime: The Effect of Social Movements on GenderBased Violence

Abstract

This paper asks whether social movements taking place on Twitter affect genderbased violence (GBV). Using Twitter data and machine learning methods, we construct a novel data set on the prevalence of Twitter conversations about GBV. We then link this data to weekly crime reports at the federal state level from the United States. We exploit the high-frequency nature of our data and an event study design to establish a causal impact of Twitter social movements on GBV. Our results point out that Twitter tweets related to GBV lead to a decrease in reported crime rates. The evidence shows that perpetrators commit these crimes less due to increased social pressure and perceived social costs. The results indicate that social media could significantly decrease reported GBV and might facilitate the signaling of social norms.