This paper is in the following e-collection/theme issue:

Infoveillance and Social Listening (273) JMIR Theme Issue: COVID-19 Special Issue (2516) Infodemiology and Infoveillance (1490) Depression and Mood Disorders; Suicide Prevention (1570) Outbreak and Pandemic Preparedness and Management (1796) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1100)

Published on in Vol 1, No 1 (2021): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26769, first published .
Monitoring Depression Trends on Twitter During the COVID-19 Pandemic: Observational Study

Monitoring Depression Trends on Twitter During the COVID-19 Pandemic: Observational Study

Monitoring Depression Trends on Twitter During the COVID-19 Pandemic: Observational Study

Authors of this article:

Yipeng Zhang1 Author Orcid Image ;   Hanjia Lyu1 Author Orcid Image ;   Yubao Liu1 Author Orcid Image ;   Xiyang Zhang2 Author Orcid Image ;   Yu Wang1 Author Orcid Image ;   Jiebo Luo1 Author Orcid Image
Article Authors Cited by (68) Tweetations (13) Metrics

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  28. Solans Noguero D, Ramírez-Cifuentes D, Ríssola E, Freire A. Gender Bias When Using Artificial Intelligence to Assess Anorexia Nervosa on Social Media: Data-Driven Study. Journal of Medical Internet Research 2023;25:e45184 View
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Books/Policy Documents

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Conference Proceedings

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  4. Liaw A, Chua H. 2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET). Depression Detection on Social Media With User Network and Engagement Features Using Machine Learning Methods View
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