Abstract
This paper introduces a new shared task for the text mining community. It aims to directly support the moderators of a youth mental health forum by asking participants to automatically triage posts into one of four severity labels: green, amber, red or crisis. The task attracted 60 submissions from 15 different teams, the best of whom achieve scores well above baselines. Their approaches and results provide valuable insights to enable moderators of peer support forums to react quickly to the most urgent, concerning content.
Cite
CITATION STYLE
Milne, D. N., Pink, G., Hachey, B., & Calvo, R. A. (2016). CLPsych 2016 shared task: Triaging content in online peer-support forums. In Proceedings of the 3rd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, CLPsych 2016 at the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2016 (pp. 118–127). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w16-0312
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