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

Methods and New Tools in Mental Health Research (454) Natural Language Processing (692) Machine Learning (1465) Mass Media/Social Media Communication and Campaigns (461) Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1514) Infoveillance and Social Listening (209) Users' and Patients' Needs for Mental Health Services (403)

Published on in Vol 9, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33685, first published .
Quantifying Changes in the Language Used Around Mental Health on Twitter Over 10 Years: Observational Study

Quantifying Changes in the Language Used Around Mental Health on Twitter Over 10 Years: Observational Study

Quantifying Changes in the Language Used Around Mental Health on Twitter Over 10 Years: Observational Study

Authors of this article:

Anne Marie Stupinski1 Author Orcid Image ;   Thayer Alshaabi1, 2 Author Orcid Image ;   Michael V Arnold1 Author Orcid Image ;   Jane Lydia Adams1, 3 Author Orcid Image ;   Joshua R Minot1 Author Orcid Image ;   Matthew Price4 Author Orcid Image ;   Peter Sheridan Dodds1, 5 Author Orcid Image ;   Christopher M Danforth1, 6 Author Orcid Image
Article Authors Cited by (9) Tweetations (19) Metrics

Journals

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  7. Yang L, Tan X, Lang R, Wang T, Li K. Reliability and validity of the Chinese version of the doomscrolling scale and the mediating role of doomscrolling in the bidirectional relationship between insomnia and depression. BMC Psychiatry 2024;24(1) View
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  9. O'Brien E, Ganjigunta R, Dhillon P. Personal Brands Versus Public Health: How Wellness Influencers Responded to COVID-19 Vaccination Efforts on Social Media (Preprint). Journal of Medical Internet Research 2024 View