Abstract
We report on the creation of a dataset for studying assessment of suicide risk via online postings in Reddit. Evaluation of risk-level annotations by experts yields what is, to our knowledge, the first demonstration of reliability in risk assessment by clinicians based on social media postings. We also introduce and demonstrate the value of a new, detailed rubric for assessing suicide risk, compare crowdsourced with expert performance, and present baseline predictive modeling experiments using the new dataset, which will be made available to researchers through the American Association of Suicidology.
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CITATION STYLE
Shing, H. C., Nair, S., Zirikly, A., Friedenberg, M., Daumé, H., & Resnik, P. (2018). Expert, crowdsourced, and machine assessment of suicide risk via online postings. In Proceedings of the 5th Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic, CLPsych 2018 at the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HTL 2018 (pp. 25–36). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w18-0603
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