Sensing the pulse of the pandemic

Unveiling the geographical and demographic disparities of public sentiment toward Covid-19 through social media

Bibliographic Data

ID12750748
AuthorsBinbin Lin (0000-0002-7013-283X, Mitchell Institute), Lei Zou (0000-0001-6206-3558, Mitchell Institute, corresponding author), Bo Zhao (0000-0002-7834-6672, University of Washington), Xiao Huang (0000-0002-4323-382X, Emory University), Heng Cai (0000-0001-6068-5150, Mitchell Institute), Mingzheng Yang (0000-0002-2936-3003, Mitchell Institute), Bing Zhou (0000-0002-8040-8182, Mitchell Institute)
Year2024
Volume51
Issue3
Pages366-384
Publication date2024-03-21
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueCartography and Geographic Information Science (JOURNAL)
Journal identifiersISSN: 1523-0406 • E-ISSN: 1545-0465
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/15230406.2024.2323489
OpenAlexW4393045222
LanguageEN
Citations received1
References cited38

Social media offers a unique lens to observe large-scale, spatial-temporal patterns of users' reactions toward critical events. However, social media use varies across demographics, with younger users being more prevalent compared to older populations. This difference introduces biases in data representativeness, and analysis based on social media without proper adjustment will lead to overlooking the voices of digitally marginalized communities and inaccurate estimations. This study explores solutions to pinpoint and alleviate the demographic biases in social media analysis through a case study estimating the public sentiment about COVID-19 using Twitter data. We analyzed the pandemic-related Twitter data in the U.S. during 2020–2021 to (1) elucidate the uneven social media usage among demographic groups and the disparities of their sentiments toward COVID-19, (2) construct an adjusted public sentiment measurement based on social media, the Sentiment Adjusted by Demographics (SAD) index, to evaluate the spatiotemporal varying public sentiment toward COVID-19. The results show higher proportions of female and adolescent Twitter users expressing negative emotions to COVID-19. The SAD index unveils that the public sentiment toward COVID-19 was most negative in January and February 2020 and most positive in April 2020. Vermont and Wyoming were the most positive and negative states toward COVID-19

2019-20 coronavirus outbreak · Coronavirus disease 2019 (COVID-19 · Economic geography · Geography · Outbreak · Pandemic · Political science · Regional science · Sentiment analysis · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Social media · Computer Science · COVID-19 Pandemic Impacts · Medicine · Misinformation and Its Impacts · Sentiment Analysis and Opinion Mining · Artificial Intelligence · Virology

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