Abstract
This preliminary analysis uses a deep LSTM neural network with fastText embeddings to predict population rates of depression on Reddit in order to estimate the effect of COVID-19 on mental health. We find that year over year, depression rates on Reddit are up 50% , suggesting a 15-million person increase in the number of depressed Americans and a $7.5 billion increase in depression related spending. This finding suggests that utility in NLP approaches to longitudinal public-health surveillance.- Anthology ID:
- 2020.nlpcovid19-acl.12
- Volume:
- Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Editors:
- Karin Verspoor, Kevin Bretonnel Cohen, Mark Dredze, Emilio Ferrara, Jonathan May, Robert Munro, Cecile Paris, Byron Wallace
- Venue:
- NLP-COVID19
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- Language:
- URL:
- https://aclanthology.org/2020.nlpcovid19-acl.12
- DOI:
- Cite (ACL):
- JT Wolohan. 2020. Estimating the effect of COVID-19 on mental health: Linguistic indicators of depression during a global pandemic. In Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020, Online. Association for Computational Linguistics.
- Cite (Informal):
- Estimating the effect of COVID-19 on mental health: Linguistic indicators of depression during a global pandemic (Wolohan, NLP-COVID19 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.nlpcovid19-acl.12.pdf