An Investigation of Suicidal Ideation from Social Media Using Machine Learning Approach
Despite improvements in the detection and treatment of severe mental disorders, suicide remains a significant public health concern. Suicide prevention and control initiatives can benefit greatly from a thorough comprehension and foreseeability of suicide patterns. Understanding suicide pattern...
Main Authors: | Soumyabrata Saha, Suparna Dasgupta, Adnan Anam, Rahul Saha, Sudarshan Nath, Surajit Dutta |
---|---|
Format: | Article |
Language: | Arabic |
Published: |
College of Science for Women, University of Baghdad
2023-06-01
|
Series: | Baghdad Science Journal |
Subjects: | |
Online Access: | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/8515 |
Similar Items
-
Predicting acute suicidal ideation on Instagram using ensemble machine learning models
by: Damien Lekkas, et al.
Published: (2021-09-01) -
Prevalence of suicidal ideation, suicidal attempt and completed suicide in Ethiopia: a systematic review and meta-analysis protocol
by: Berhanu Boru Bifftu, et al.
Published: (2019-03-01) -
Message similarity as a proxy to repetitive thinking: Associations with non-suicidal self-injury and suicidal ideation on social media
by: Anton Malko, et al.
Published: (2023-08-01) -
Investigating mental health status and prevalence of suicidal ideation in the elderly
by: Ameneh Jafari Nodolaghi, et al.
Published: (2019-09-01) -
Elucidating the chronic, complex nature of suicidal ideation: A national qualitative study of veterans with a recent suicide attempt
by: Lauren M. Denneson, et al.
Published: (2020-12-01)