Sensing the Pulse of the Pandemic: Geovisualizing the Demographic Disparities of Public Sentiment toward COVID-19 through Social Media
Binbin Lina, Lei Zoua, Bo Zhao, Xiao Huang, Heng Cai, Mingzheng Yang,, and Bing Zhou

TL;DR
This paper develops a demographic-adjusted sentiment index using Twitter data to accurately assess public sentiment toward COVID-19 across different regions and demographics in the U.S., addressing biases in social media analysis.
Contribution
It introduces the Sentiment Adjusted by Demographics (SAD) index to correct for demographic biases in social media sentiment analysis during the pandemic.
Findings
Higher negative sentiment among female and adolescent Twitter users.
Public sentiment was most negative in early 2020 and most positive in April 2020.
Vermont and Wyoming showed the most positive and negative sentiments, respectively.
Abstract
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…
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Taxonomy
TopicsMisinformation and Its Impacts · COVID-19 epidemiological studies · COVID-19 and Mental Health
