Text-Based Depression Prediction on Social Media Using Machine Learning: Systematic Review and Meta-Analysis.

Journal: Journal of medical Internet research
PMID: 40215481

Abstract

BACKGROUND: Depression affects more than 350 million people globally. Traditional diagnostic methods have limitations. Analyzing textual data from social media provides new insights into predicting depression using machine learning. However, there is a lack of comprehensive reviews in this area, which necessitates further research.

Authors

  • Doreen Phiri
    School of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan.
  • Frank Makowa
    Department of Information and Communication Technology, University of North Carolina Project, Lilongwe, Malawi.
  • Vivi Leona Amelia
    School of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan.
  • Yohane Vincent Abero Phiri
    Department of Epidemiology and Environmental Health, University at Buffalo, New York, NY, United States.
  • Lindelwa Portia Dlamini
    School of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan.
  • Min-Huey Chung
    School of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan.

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