Identifying pandemic-related stress factors from social-media posts – Effects on students and young-adults

Sachin Thukral, Suyash Sangwan, Arnab Chatterjee, Lipika Dey


Abstract
The COVID-19 pandemic has thrown natural life out of gear across the globe. Strict measures are deployed to curb the spread of the virus that is causing it, and the most effective of them have been social isolation. This has led to wide-spread gloom and depression across society but more so among the young and the elderly. There are currently more than 200 million college students in 186 countries worldwide, affected due to the pandemic. The mode of education has changed suddenly, with the rapid adaptation of e-learning, whereby teaching is undertaken remotely and on digital platforms. This study presents insights gathered from social media posts that were posted by students and young adults during the COVID times. Using statistical and NLP techniques, we analyzed the behavioural issues reported by users themselves in their posts in depression related communities on Reddit. We present methodologies to systematically analyze content using linguistic techniques to find out the stress-inducing factors. Online education, losing jobs, isolation from friends and abusive families emerge as key stress factors
Anthology ID:
2020.nlpcovid19-2.23
Volume:
Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020
Month:
December
Year:
2020
Address:
Online
Venues:
EMNLP | NLP-COVID19
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
Language:
URL:
https://www.aclweb.org/anthology/2020.nlpcovid19-2.23
DOI:
10.18653/v1/2020.nlpcovid19-2.23
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.nlpcovid19-2.23.pdf