ConvSent at CLPsych 2019 Task A: Using Post-level Sentiment Features for Suicide Risk Prediction on Reddit

Kristen Allen, Shrey Bagroy, Alex Davis, Tamar Krishnamurti


Abstract
This work aims to infer mental health status from public text for early detection of suicide risk. It contributes to Shared Task A in the 2019 CLPsych workshop by predicting users’ suicide risk given posts in the Reddit subforum r/SuicideWatch. We use a convolutional neural network to incorporate LIWC information at the Reddit post level about topics discussed, first-person focus, emotional experience, grammatical choices, and thematic style. In sorting users into one of four risk categories, our best system’s macro-averaged F1 score was 0.50 on the withheld test set. The work demonstrates the predictive power of the Linguistic Inquiry and Word Count dictionary, in conjunction with a convolutional network and holistic consideration of each post and user.
Anthology ID:
W19-3024
Volume:
Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Venues:
CLPsych | NAACL | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
182–187
Language:
URL:
https://www.aclweb.org/anthology/W19-3024
DOI:
10.18653/v1/W19-3024
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PDF:
http://aclanthology.lst.uni-saarland.de/W19-3024.pdf