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

Early Results in Infodemiology and Infoveillance (69) Artificial Intelligence (1328) Natural Language Processing (677) Depression and Mood Disorders; Suicide Prevention (1341) Mass Media/Social Media Communication and Campaigns (458) Infodemiology and Infoveillance (1333) Linguistics, Comprehension, and Learning (52)

Published on in Vol 6, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35563, first published .
Analyzing Suicide Risk From Linguistic Features in Social Media: Evaluation Study

Analyzing Suicide Risk From Linguistic Features in Social Media: Evaluation Study

Analyzing Suicide Risk From Linguistic Features in Social Media: Evaluation Study

Authors of this article:

Cecilia Lao1 Author Orcid Image ;   Jo Lane2 Author Orcid Image ;   Hanna Suominen1, 3 Author Orcid Image
Article Authors Cited by (7) Tweetations (6) Metrics

Cecilia Lao   1 , BA, BACMP (Hons) ;   Jo Lane   2 , PhD ;   Hanna Suominen   1, 3 , MSc, MEdL, PhD, Docent (Adj/Professor)

1 School of Computing, College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia

2 National Centre for Epidemiology and Population Health, College of Health and Medicine, The Australian National University, Canberra, ACT, Australia

3 Department of Computing, Faculty of Technology, University of Turku, Turku, Finland

Corresponding Author:

  • Cecilia Lao, BA, BACMP (Hons)
  • School of Computing
  • College of Engineering and Computer Science
  • The Australian National University
  • 145 Science Road
  • Canberra, ACT, 2600
  • Australia
  • Phone: 61 416236920
  • Email: cecilia.lao@anu.edu.au