Social media offers a unique lens to observe users emotions and subjective
feelings toward critical events or topics and has been widely used to
investigate public sentiment during crises, e.g., the COVID-19 pandemic.
However, social media use varies across demographic groups, with younger people
being more inclined to use social media than the older population. This digital
divide could lead to biases in data representativeness and analysis results,
causing a persistent challenge in research based on social media data. This
study aims to tackle this challenge through a case study of estimating the
public sentiment about the COVID-19 using social media data. We analyzed the
pandemic-related Twitter data in the United States from January 2020 to
December 2021. The objectives are: (1) to elucidate the uneven social media
usage among various demographic groups and the disparities of their emotions
toward COVID-19, (2) to construct an unbiased measurement for public sentiment
based on social media data, the Sentiment Adjusted by Demographics (SAD) index,
through the post-stratification method, and (3) to evaluate the spatially and
temporally evolved public sentiment toward COVID-19 using the SAD index. The
results show significant discrepancies among demographic groups in their
COVID-19-related emotions. Female and under or equal to 18 years old Twitter
users expressed long-term negative sentiment toward COVID-19. The proposed SAD
index in this study corrected the underestimation of negative sentiment in 31
states, especially in Vermont. According to the SAD index, Twitter users in
Wyoming (Vermont) posted the largest (smallest) percentage of negative tweets
toward the pandemic