Mental health effects of COVID-19 lockdowns: a Twitter-based analysis

Sara Colella (1) , Frédéric Dufourt (1) , Vincent A Hildebrand (2, 3) , Rémi Vivès (2)

1 AMSE - Aix-Marseille Sciences Economiques
2 York University [Toronto]
3 Dalla Lana School of Public Health, University of Toronto

We derive a mental health indicator measuring the frequency of words expressing anger, anxiety and sadness from a fixed population of Twitter users located in France. During the first COVID-19 lockdown, our indicator did not reveal a statistically significant mental health response, while the second lockdown triggered a sharp and persistent deterioration in all three emotions. In addition, DID and event study estimates show a more severe mental health deterioration among women and younger users during the second lockdown. Our results suggest that successive stay-at-home orders significantly worsen mental health across a large segment of the population.

Keywords: COVID-19; lockdown; mental health; Twitter data; well-being

Domains: Economics and Finance

Sara Colella, Frédéric Dufourt, Vincent A Hildebrand, Rémi Vivès. Mental health effects of COVID-19 lockdowns: a Twitter-based analysis. 2022. ⟨hal-03740701⟩