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

Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1512) Natural Language Processing (688) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1639) Machine Learning (1458) Infodemiology and Infoveillance (1349) Diagnostic Tools in Mental Health (241)

Published on in Vol 24, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34705, first published .
Detecting Potentially Harmful and Protective Suicide-Related Content on Twitter: Machine Learning Approach

Detecting Potentially Harmful and Protective Suicide-Related Content on Twitter: Machine Learning Approach

Detecting Potentially Harmful and Protective Suicide-Related Content on Twitter: Machine Learning Approach

Authors of this article:

Hannah Metzler1, 2, 3, 4, 5 Author Orcid Image ;   Hubert Baginski3, 6 Author Orcid Image ;   Thomas Niederkrotenthaler2 Author Orcid Image ;   David Garcia1, 3, 4 Author Orcid Image
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