Bibliometric Studies and the Discipline of Social Media Mental Health Research. Comment on "Machine Learning for Mental Health in Social Media: Bibliometric Study"
- PMID: 34137722
- PMCID: PMC8277321
- DOI: 10.2196/28990
Bibliometric Studies and the Discipline of Social Media Mental Health Research. Comment on "Machine Learning for Mental Health in Social Media: Bibliometric Study"
Keywords: bibliometric analysis; bibliometrics; machine learning; mental health; social media.
Conflict of interest statement
Conflicts of Interest: GC is a stockholder and employee of Qntfy.
Comment in
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Authors' Reply to: Bibliometric Studies and the Discipline of Social Media Mental Health Research. Comment on "Machine Learning for Mental Health in Social Media: Bibliometric Study".J Med Internet Res. 2021 Jun 17;23(6):e29549. doi: 10.2196/29549. J Med Internet Res. 2021. PMID: 34137721 Free PMC article. No abstract available.
Comment on
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Machine Learning for Mental Health in Social Media: Bibliometric Study.J Med Internet Res. 2021 Mar 8;23(3):e24870. doi: 10.2196/24870. J Med Internet Res. 2021. PMID: 33683209 Free PMC article. Review.
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Authors' Reply to: Bibliometric Studies and the Discipline of Social Media Mental Health Research. Comment on "Machine Learning for Mental Health in Social Media: Bibliometric Study".J Med Internet Res. 2021 Jun 17;23(6):e29549. doi: 10.2196/29549. J Med Internet Res. 2021. PMID: 34137721 Free PMC article. No abstract available.
References
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- Kim J, Lee Daeun, Park Eunil. Machine Learning for Mental Health in Social Media: Bibliometric Study. J Med Internet Res. 2021 Mar 08;23(3):e24870. doi: 10.2196/24870. https://www.jmir.org/2021/3/e24870/ - DOI - PMC - PubMed
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- Ernala SK, Birnbaum ML, Michael L, Candan KA, Rizvi AF, Sterling WA, Kane JM. Methodological Gaps in Predicting Mental Health States from Social Media: Triangulating Diagnostic Signals. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems; CHI '19: CHI Conference on Human Factors in Computing Systems; May 4-9; Glasgow, Scotland, UK. New York, NY: Association for Computing Machinery; 2019. pp. 1–16. - DOI
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- Lee EE, Torous John, De Choudhury Munmun, Depp Colin A, Graham Sarah A, Kim Ho-Cheol, Paulus Martin P, Krystal John H, Jeste Dilip V. Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom. Biol Psychiatry Cogn Neurosci Neuroimaging. 2021 Feb 08; doi: 10.1016/j.bpsc.2021.02.001. - DOI - PMC - PubMed
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