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Identifying Chinese Microblog Users With High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model.

Li GuanBibo HaoChenhong PengPaul Siu-Fai YipTingshao Zhu
Published in: JMIR mental health (2015)
Individuals in China with high suicide probability are recognizable by profile and text-based information from microblogs. Although there is still much space to improve the performance of classification models in the future, this study may shed light on preliminary screening of risky individuals via machine learning algorithms, which can work side-by-side with expert scrutiny to increase efficiency in large-scale-surveillance of suicide probability from online social media.
Keyphrases
  • machine learning
  • social media
  • health information
  • deep learning
  • artificial intelligence
  • big data
  • public health
  • healthcare
  • current status