Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Oct 8, 2020
Date Accepted: Feb 17, 2021
Scientific Analysis on Machine Learning for Mental Health in Social Media: A Bibliometric Study
ABSTRACT
Background:
Social media provides easily accessible and time saving communication approach for individuals with mental disorders compared to face-to-face meetings with medical providers. Recently, machine learning (ML) based mental health exploration using large-scale social media data has attracted significant attention.
Objective:
We aim to provide a bibliometric analysis and discussion on research trends of ML and mental health in social media.
Methods:
Publications addressing social media and ML in the field of mental health are retrieved from Scopus and Web of Science (WoS). We analyzed the publication distribution to measure productivity on sources, countries, affiliations, authors, and research subjects, and visualized the keyword co-occurrence network. The research methodologies of previous studies with high citations have also been thoroughly described.
Results:
We obtained a total of 565 papers published from 2015 to 2020. In the last five years, the number of publications has demonstrated continuous growth with two most productive publications, Lecture Notes in Computer Science and Journal of Medical Internet Research, with consideration of Scopus and WoS. In addition, notable methodological approaches with data resources presented in high-rank publications were investigated.
Conclusions:
Based on the results, both the comprehensive overview and implications are presented. Moreover, we provided valuable insights for future considerable issues of ML and mental health in social media.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.