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

Siqin WangHuan NingXiao HuangYunyu XiaoMengxi ZhangEllie Fan YangYukio SadahiroYan LiuZhenlong LiTao HuXiaokang FuZi LiYe Zeng
Published in: Journal of medical Internet research (2023)
Social media platforms provide an anonymous space where people express their suicidal thoughts, ideation, and acts. Such expressions can serve as an alternative source to estimating and predicting suicide in countries without reliable suicide statistics. It can also provide real-time tracking of suicide risks, serving as an early warning for suicide. The identification of areas where suicide risks are highly concentrated is crucial for location-based mental health planning, enabling suicide prevention and intervention through social media in a spatially and temporally explicit manner.
Keyphrases
  • social media
  • health information
  • mental health
  • deep learning
  • randomized controlled trial
  • healthcare
  • public health
  • mental illness
  • human health
  • bioinformatics analysis
  • climate change
  • drug induced
  • adverse drug