Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/266258 
Year of Publication: 
2022
Series/Report no.: 
ifo Working Paper No. 381
Publisher: 
ifo Institute - Leibniz Institute for Economic Research at the University of Munich, Munich
Abstract: 
This paper asks whether social movements taking place on Twitter affect gender-based 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.
Subjects: 
Economics of gender
US
domestic abuse
public policy
criminal law
illegal behavior and the enforcement of law
JEL: 
J12
J16
J78
K14
K42
O51
Document Type: 
Working Paper

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