Abstract
We reframe suicide risk assessment from social media as a ranking problem whose goal is maximizing detection of severely at-risk individuals given the time available. Building on measures developed for resource-bounded document retrieval, we introduce a well founded evaluation paradigm, and demonstrate using an expert-annotated test collection that meaningful improvements over plausible cascade model baselines can be achieved using an approach that jointly ranks individuals and their social media posts.- Anthology ID:
- 2020.acl-main.723
- Volume:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Editors:
- Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 8124–8137
- Language:
- URL:
- https://preview.aclanthology.org/add_missing_videos/2020.acl-main.723/
- DOI:
- 10.18653/v1/2020.acl-main.723
- Cite (ACL):
- Han-Chin Shing, Philip Resnik, and Douglas Oard. 2020. A Prioritization Model for Suicidality Risk Assessment. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 8124–8137, Online. Association for Computational Linguistics.
- Cite (Informal):
- A Prioritization Model for Suicidality Risk Assessment (Shing et al., ACL 2020)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2020.acl-main.723.pdf