Opportunities and challenges of using social media big data to assess mental health consequences of the COVID-19 crisis and future major events

Autor: Martin Tušl, Anja Thelen, Kailing Marcus, Alexandra Peters, Evgeniya Shalaeva, Benjamin Scheckel, Martin Sykora, Suzanne Elayan, John A. Naslund, Ketan Shankardass, Stephen J. Mooney, Marta Fadda, Oliver Gruebner
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Discover Mental Health, Vol 2, Iss 1, Pp 1-6 (2022)
Druh dokumentu: article
ISSN: 2731-4383
DOI: 10.1007/s44192-022-00017-y
Popis: Abstract The present commentary discusses how social media big data could be used in mental health research to assess the impact of major global crises such as the COVID-19 pandemic. We first provide a brief overview of the COVID-19 situation and the challenges associated with the assessment of its global impact on mental health using conventional methods. We then propose social media big data as a possible unconventional data source, provide illustrative examples of previous studies, and discuss the advantages and challenges associated with their use for mental health research. We conclude that social media big data represent a valuable resource for mental health research, however, several methodological limitations and ethical concerns need to be addressed to ensure safe use.
Databáze: Directory of Open Access Journals
Externí odkaz: