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

Sara Colella (sara5colella@gmail.com), Frédéric Dufourt, Vincent Hildebrand and Rémi Vivès (rvives@yorku.ca)
Additional contact information
Sara Colella: Aix-Marseille Univ, CNRS, AMSE, Marseille, France., https://www.amse-aixmarseille.fr/en/membres/colella
Rémi Vivès: Glendon College, York University, https://www.glendon.yorku.ca/fr/profil-details/?currentuserid=844370

No 2218, AMSE Working Papers from Aix-Marseille School of Economics, France

Abstract: We use a distinctive methodology that leverages a fixed population of Twitter users located in France to gauge the mental health effects of repeated lockdown orders. To do so, we derive from our population a mental health indicator that measures the frequency of words expressing anger, anxiety and sadness. Our indicator did not reveal a statistically significant mental health response during the first lockdown, while the second lockdown triggered a sharp and persistent deterioration in all three emotions. Our estimates also show a more severe deterioration in mental health among women and younger users during the second lockdown. These results suggest that successive stay-at-home orders significantly worsen mental health across a large segment of the population. We also show that individuals who are closer to their social network were partially protected by this network during the first lockdown, but were no longer protected during the second, demonstrating the gravity of successive lockdowns for mental health.

Keywords: COVID-19; lockdown; mental health; Twitter data; well-being (search for similar items in EconPapers)
JEL-codes: C81 I12 I18 I31 (search for similar items in EconPapers)
Pages: 61 pages
Date: 2022-07, Revised 2023-09
New Economics Papers: this item is included in nep-hea
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Mental health effects of COVID-19 lockdowns: A Twitter-based analysis (2023)
Working Paper: Mental health effects of COVID-19 lockdowns: a Twitter-based analysis (2023)
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