Temporal Mental Health Dynamics on Social Media

August 30, 2020 ยท Declared Dead ยท ๐Ÿ› NLP4COVID@EMNLP

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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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