Abstract
BackgroundAs policy makers continue to shape the national and local responses to the COVID-19 pandemic, the information they choose to share and how they frame their content provide key insights into the public and health care systems.ObjectiveWe examined the language used by the members of the US House and Senate during the first 10 months of the COVID-19 pandemic and measured content and sentiment based on the tweets that they shared.MethodsWe used Quorum (Quorum Analytics Inc) to access more than 300,000 tweets posted by US legislators from January 1 to October 10, 2020. We used differential language analyses to compare the content and sentiment of tweets posted by legislators based on their party affiliation.ResultsWe found that health care–related themes in Democratic legislators’ tweets focused on racial disparities in care (odds ratio [OR] 2.24, 95% CI 2.22-2.27; P<.001), health care and insurance (OR 1.74, 95% CI 1.7-1.77; P<.001), COVID-19 testing (OR 1.15, 95% CI 1.12-1.19; P<.001), and public health guidelines (OR 1.25, 95% CI 1.22-1.29; P<.001). The dominant themes in the Republican legislators’ discourse included vaccine development (OR 1.51, 95% CI 1.47-1.55; P<.001) and hospital resources and equipment (OR 1.22, 95% CI 1.18-1.25). Nonhealth care–related topics associated with a Democratic affiliation included protections for essential workers (OR 1.55, 95% CI 1.52-1.59), the 2020 election and voting (OR 1.31, 95% CI 1.27-1.35), unemployment and housing (OR 1.27, 95% CI 1.24-1.31), crime and racism (OR 1.22, 95% CI 1.18-1.26), public town halls (OR 1.2, 95% CI 1.16-1.23), the Trump Administration (OR 1.22, 95% CI 1.19-1.26), immigration (OR 1.16, 95% CI 1.12-1.19), and the loss of life (OR 1.38, 95% CI 1.35-1.42). The themes associated with the Republican affiliation included China (OR 1.89, 95% CI 1.85-1.92), small business assistance (OR 1.27, 95% CI 1.23-1.3), congressional relief bills (OR 1.23, 95% CI 1.2-1.27), press briefings (OR 1.22, 95% CI 1.19-1.26), and economic recovery (OR 1.2, 95% CI 1.16-1.23).ConclusionsDivergent language use on social media corresponds to the partisan divide in the first several months of the course of the COVID-19 public health crisis.
Highlights
The novel COVID-19 pandemic continues to surge throughout the world
We extracted the relative frequency of single words and phrases from tweets by using the Differential Language Analysis ToolKit package [8] and created two sets of features—(1) an open vocabulary that was defined by using latent Dirichlet allocation [9], an unsupervised clustering algorithm, to create 50 data-driven word clusters and (2) sentiment, which was measured by using the National Research Council (NRC) Canada lexicon [10], a data-driven dictionary containing words associated with positive and negative valence
By using machine learning techniques, we investigated narrative content in over 300,000 twitter posts from US legislators over the course of the COVID-19 pandemic to date
Summary
The novel COVID-19 pandemic continues to surge throughout the world. The United States’ federal and state policy responses continue to shift and vary throughout the stages of the pandemic [1]. Understanding what content US legislators are sharing through social media posts (eg, Twitter) and how they are relaying COVID-19–related information is important, as these issues guide public knowledge and public opinion and inform policy change. As policy makers continue to shape the national and local responses to the COVID-19 pandemic, the information they choose to share and how they frame their content provide key insights into the public and health care systems. Objective: We examined the language used by the members of the US House and Senate during the first 10 months of the COVID-19 pandemic and measured content and sentiment based on the tweets that they shared. We used differential language analyses to compare the content and sentiment of tweets posted by legislators based on their party affiliation. Conclusions: Divergent language use on social media corresponds to the partisan divide in the first several months of the course of the COVID-19 public health crisis
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