TY - GEN
T1 - Using Tweets to Assess Mental Well-being of Essential Workers during the COVID-19 Pandemic
AU - Blair, Johnna
AU - Hsu, Chi Yang
AU - Qiu, Ling
AU - Huang, Shih Hong
AU - Huang, Ting Hao Kenneth
AU - Abdullah, Saeed
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/5/8
Y1 - 2021/5/8
N2 - The Covid-19 pandemic has led to large-scale lifestyle changes and increased social isolation and stress on a societal level. This has had a unique impact on US "essential workers"(EWs) - who continue working outside their homes to provide critical services, such as hospital and infrastructure employees. We examine the use of Twitter by EWs as a step toward understanding the pandemic's impact on their mental well-being, as compared to the population as a whole. We found that EWs authored a higher ratio of mental health related tweets during the pandemic than the average user, but authored fewer tweets with Covid related keywords than average users. Despite this, sentiment analysis showed that, on average, EWs' tweets yield a more positive sentiment score than average Twitter users, both before and during the pandemic. Based on these initial insights, we highlight our future aims to investigate individual differences in this impact to EWs.
AB - The Covid-19 pandemic has led to large-scale lifestyle changes and increased social isolation and stress on a societal level. This has had a unique impact on US "essential workers"(EWs) - who continue working outside their homes to provide critical services, such as hospital and infrastructure employees. We examine the use of Twitter by EWs as a step toward understanding the pandemic's impact on their mental well-being, as compared to the population as a whole. We found that EWs authored a higher ratio of mental health related tweets during the pandemic than the average user, but authored fewer tweets with Covid related keywords than average users. Despite this, sentiment analysis showed that, on average, EWs' tweets yield a more positive sentiment score than average Twitter users, both before and during the pandemic. Based on these initial insights, we highlight our future aims to investigate individual differences in this impact to EWs.
UR - http://www.scopus.com/inward/record.url?scp=85105818347&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85105818347&partnerID=8YFLogxK
U2 - 10.1145/3411763.3451612
DO - 10.1145/3411763.3451612
M3 - Conference contribution
AN - SCOPUS:85105818347
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, CHI EA 2021
PB - Association for Computing Machinery
T2 - 2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI EA 2021
Y2 - 8 May 2021 through 13 May 2021
ER -