Temporal Mental Health Dynamics on Social Media
August 30, 2020 ยท Declared Dead ยท ๐ NLP4COVID@EMNLP
"No code URL or promise found in abstract"
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Authors
Tom Tabak, Matthew Purver
arXiv ID
2008.13121
Category
cs.CL: Computation & Language
Cross-listed
cs.IR,
cs.SI
Citations
13
Venue
NLP4COVID@EMNLP
Last Checked
5 months ago
Abstract
We describe a set of experiments for building a temporal mental health dynamics system. We utilise a pre-existing methodology for distant-supervision of mental health data mining from social media platforms and deploy the system during the global COVID-19 pandemic as a case study. Despite the challenging nature of the task, we produce encouraging results, both explicit to the global pandemic and implicit to a global phenomenon, Christmas Depression, supported by the literature. We propose a methodology for providing insight into temporal mental health dynamics to be utilised for strategic decision-making.
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