Public Surveillance of Social Media for Suicide Using Advanced Deep Learning Models in Japan: Time Series Study From 2012 to 2022.

Journal: Journal of medical Internet research
Published Date: Jun 2, 2023

Abstract

BACKGROUND: Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people's expressions on social media. However, there is not enough evidence to conclude that social media provides public surveillance for suicide without aligning suicide risks detected on social media with actual suicidal behaviors. Corroborating this alignment is a crucial foundation for suicide prevention and intervention through social media and for estimating and predicting suicide in countries with no reliable suicide statistics.

Authors

  • Siqin Wang
    Graduate School of Interdisciplinary Information Studies, University of Tokyo, Tokyo, Japan.
  • Huan Ning
    Department of Geography, University of South Carolina, Columbia, SC, United States.
  • Xiao Huang
    Department of Anesthesiology, Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Workers' Stadium South Road, Beijing 100020, Chaoyang Distinct, China.
  • Yunyu Xiao
    Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
  • Mengxi Zhang
    Department of Biomedical Engineering, University of California, Davis, CA, USA.
  • Ellie Fan Yang
    School of Communication and Mass Media, Northwest Missouri State University, Maryville, MO, United States.
  • Yukio Sadahiro
    Graduate School of Interdisciplinary Information Studies, University of Tokyo, Tokyo, Japan.
  • Yan Liu
    Department of Clinical Microbiology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200072, People's Republic of China.
  • Zhenlong Li
    Geoinformation and Big Data Research Laboratory, Department of Geography, University of South Carolina, Columbia, SC, USA.
  • Tao Hu
    Department of Preventive Dentistry, State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China.
  • Xiaokang Fu
    Centre for Geographic Analysis, Harvard University, Cambridge, MA, United States.
  • Zi Li
    Department of Nephrology, Institute of Nephrology, West China Hospital of Sichuan University, Chengdu, China.
  • Ye Zeng
    Department of Medical Business, Nihon Pharmaceutical University, Tokyo, Japan.

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