Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/282302 
Year of Publication: 
2023
Series/Report no.: 
Quaderni - Working Paper DSE No. 1180
Publisher: 
Alma Mater Studiorum - Università di Bologna, Dipartimento di Scienze Economiche (DSE), Bologna
Abstract: 
This paper studies how discriminatory fake news arises and spatially diffuses. We focus on India at the onset of the COVID-19 pandemic: on March 30, a Muslim convention (the Tablighi Jamaat) in New Delhi became publicly recognized as a COVID hotspot, and the next day, fake news on Muslims intentionally spreading the virus spiked. Using Twitter data, we build a comprehensive novel dataset of georeferenced tweets to identify anti-Muslim fake news. We find, in cross-sectional and difference-in-difference settings, that discriminatory fake news became much more widespread after March 30 (1) in New Delhi, (2) in districts closer to New Delhi, and (3) in districts with higher social media interactions with New Delhi. Further, we investigate whether deeply rooted historical factors may have also played a role in the diffusion of anti-Muslim fake news: we show that, after March 30, discriminatory fake news was more common in districts historically exposed to attacks by Muslim groups.
Subjects: 
discrimination
fake news
religion
covid
india
JEL: 
J15
Z12
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Working Paper

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