This paper is in the following e-collection/theme issue:

Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1514) Natural Language Processing (692) Depression and Mood Disorders; Suicide Prevention (1363) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Machine Learning (1465)

Published on in Vol 19, No 7 (2017): July

Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study

Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study

Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study

Authors of this article:

Qijin Cheng1 Author Orcid Image ;   Tim MH Li2 Author Orcid Image ;   Chi-Leung Kwok1 Author Orcid Image ;   Tingshao Zhu3 Author Orcid Image ;   Paul SF Yip1 Author Orcid Image
Article Authors Cited by (146) Tweetations (18) Metrics

Qijin Cheng   1 , PhD ;   Tim MH Li   2 , PhD ;   Chi-Leung Kwok   1 , PhD ;   Tingshao Zhu   3 , PhD ;   Paul SF Yip   1 , PhD

1 HKJC Center for Suicide Research and Prevention, The University of Hong Kong, Hong Kong, China (Hong Kong)

2 Department of Paediatrics & Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China (Hong Kong)

3 Institute of Psychology & Insititute of Computing Technology, Chinese Academy of Sciences, Beijing, China

Corresponding Author:

  • Qijin Cheng, PhD
  • HKJC Center for Suicide Research and Prevention
  • The University of Hong Kong
  • 2/F, The Hong Kong Jockey Club Building for Interdisciplinary Research, 5 Sassoon Road, Pokfulam, Hong Kong
  • Hong Kong
  • China (Hong Kong)
  • Phone: 852 2831-5232
  • Fax: 852 2549-7161
  • Email: chengqj@connect.hku.hk