Sharath Chandra Guntuku1,2,3, Jonathan Purtle4, Zachary F Meisel5,3,6, Raina M Merchant5,2,3,6, Anish Agarwal5,2,3,6. 1. Department of Computer and Information Science, University of Pennsylvania, 3300 Walnut St, Philadelphia, US. 2. Penn Medicine Center for Digital Health, University of Pennsylvania, Philadelphia, US. 3. Leonard Davis Institute of Health Economics, University of Pennsylvania, 3641 Locust Walk, Philadelphia, US. 4. Department of Health Management & Policy, Drexel University Dornsife School of Public Health, Philadelphia, US. 5. Department of Emergency Medicine, University of Pennsylvania, Philadelphia, US. 6. Center for Emergency Care Research and Policy, University of Pennsylvania, Philadelphia, US.
Abstract
BACKGROUND: As policy makers continue to shape the national and local responses to the COVID-19 pandemic, information they choose to share, and how they frame their content provides key insights to the public and healthcare systems. OBJECTIVE: We examine the language used by the members of the U.S. House and Senate during the first ten months of the COVID-19 pandemic, measuring the content and sentiment based on the tweets they shared. METHODS: We used Quorum to access more than 300,000 tweets posted by U.S. legislators from January 1 to October 10, 2020. We used differential language analyses to compare the content and sentiment of tweets posted by legislators by their party affiliation. RESULTS: We find that healthcare related themes in Democrat legislators focus on racial disparities in care (Odds-Ratio, OR 2.24, p<0.001), healthcare and insurance (OR 1.74, p<0.001), COVID-19 testing (OR 1.15, p<0.001), and public health guidelines (OR 1.25, p<0.001), those dominant in the republican legislators' discourse included: vaccine development (OR 1.51, p<0.001) and hospital resources and equipment (OR 1.22). Non healthcare related topics associated with Democratic affiliation included: Protections for Essential Workers (OR 1.55), 2020 Election and Voting (OR 1.31), Unemployment and Housing (OR 1.27), Crime/Racism (OR 1.22), Public Town Halls (OR 1.2), Trump Administration (OR 1.22), Immigration (OR 1.16), and Loss of Life (OR 1.38). Themes associated with Republican affiliation included: China (OR 1.87), Small Business Assistance (OR 1.27), Congressional Relief Bills (OR 1.23), Press Briefings (OR 1.22), and Economic Recovery (OR 1.2). CONCLUSIONS: Divergent language use on social media corresponds to the partisan divide in several months over the course of the public health crisis.
BACKGROUND: As policy makers continue to shape the national and local responses to the COVID-19 pandemic, information they choose to share, and how they frame their content provides key insights to the public and healthcare systems. OBJECTIVE: We examine the language used by the members of the U.S. House and Senate during the first ten months of the COVID-19 pandemic, measuring the content and sentiment based on the tweets they shared. METHODS: We used Quorum to access more than 300,000 tweets posted by U.S. legislators from January 1 to October 10, 2020. We used differential language analyses to compare the content and sentiment of tweets posted by legislators by their party affiliation. RESULTS: We find that healthcare related themes in Democrat legislators focus on racial disparities in care (Odds-Ratio, OR 2.24, p<0.001), healthcare and insurance (OR 1.74, p<0.001), COVID-19 testing (OR 1.15, p<0.001), and public health guidelines (OR 1.25, p<0.001), those dominant in the republican legislators' discourse included: vaccine development (OR 1.51, p<0.001) and hospital resources and equipment (OR 1.22). Non healthcare related topics associated with Democratic affiliation included: Protections for Essential Workers (OR 1.55), 2020 Election and Voting (OR 1.31), Unemployment and Housing (OR 1.27), Crime/Racism (OR 1.22), Public Town Halls (OR 1.2), Trump Administration (OR 1.22), Immigration (OR 1.16), and Loss of Life (OR 1.38). Themes associated with Republican affiliation included: China (OR 1.87), Small Business Assistance (OR 1.27), Congressional Relief Bills (OR 1.23), Press Briefings (OR 1.22), and Economic Recovery (OR 1.2). CONCLUSIONS: Divergent language use on social media corresponds to the partisan divide in several months over the course of the public health crisis.
Authors: Eden Engel-Rebitzer; Daniel C Stokes; Zachary F Meisel; Jonathan Purtle; Rebecca Doyle; Alison M Buttenheim Journal: JMIR Infodemiology Date: 2022-02-18