A Prioritization Model for Suicidality Risk Assessment

Han-Chin Shing, Philip Resnik, Douglas Oard


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://aclanthology.org/2020.acl-main.723
DOI:
10.18653/v1/2020.acl-main.723
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2020.acl-main.723.pdf
Video:
 http://slideslive.com/38929150