Weakly-Supervised Methods for Suicide Risk Assessment: Role of Related Domains
This work addresses the challenge of small labeled datasets for suicide risk assessment on social media, which is an incremental improvement for mental health monitoring applications.
The authors tackled the problem of limited labeled data for suicide risk assessment on Reddit by investigating weakly-supervised methods, showing that pseudo-labeling using related mental health domains like anxiety and depression improves model performance.
Social media has become a valuable resource for the study of suicidal ideation and the assessment of suicide risk. Among social media platforms, Reddit has emerged as the most promising one due to its anonymity and its focus on topic-based communities (subreddits) that can be indicative of someone's state of mind or interest regarding mental health disorders such as r/SuicideWatch, r/Anxiety, r/depression. A challenge for previous work on suicide risk assessment has been the small amount of labeled data. We propose an empirical investigation into several classes of weakly-supervised approaches, and show that using pseudo-labeling based on related issues around mental health (e.g., anxiety, depression) helps improve model performance for suicide risk assessment.