Event Detection for Suicide Understanding

Anonymous

Paper Link: https://openreview.net/forum?id=jOZWKPtPgk

Paper Type: Short paper (up to four pages of content + unlimited references and appendices)

Abstract: Suicide is a serious problem in every society. Understanding life events of a potential patient is essential for successful suicide-risk assessment and prevention. In this work, we focus on the Event Detection (ED) task to identify event trigger words of suicide-related events in public posts of discussion forums. In particular, we introduce SuicideED: a new dataset for the ED task that features seven suicidal event types to comprehensively capture suicide actions and ideation, and general risk and protective factors. Our experiments with current state-of-the-art ED systems suggest that this domain poses meaningful challenges as there is significant room for improvement of ED models. We will release SuicideED to support future research in this important area.

Presentation Mode: This paper will be presented in person in Seattle

Copyright Consent Signature (type Name Or NA If Not Transferrable): Thien Huu Nguyen

Copyright Consent Name And Address: Thien Huu Nguyen, 330, Deschutes Hall, University of Oregon, 1477 E. 13th Avenue, Eugene, OR 97403, USA