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COVID-19 Misinformation and Polarization on Twitter: #StayHome, #Plandemic, and Health Communication

COVID-19 Misinformation and Polarization on Twitter: #StayHome, #Plandemic, and Health Communication

Rebecca Godard, Susan Holtzman
Copyright: © 2021 |Volume: 13 |Issue: 1 |Pages: 18
ISSN: 2642-2247|EISSN: 2642-2255|EISBN13: 9781799863984|DOI: 10.4018/IJSMOC.2021010102
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MLA

Godard, Rebecca, and Susan Holtzman. "COVID-19 Misinformation and Polarization on Twitter: #StayHome, #Plandemic, and Health Communication." IJSMOC vol.13, no.1 2021: pp.1-18. http://doi.org/10.4018/IJSMOC.2021010102

APA

Godard, R. & Holtzman, S. (2021). COVID-19 Misinformation and Polarization on Twitter: #StayHome, #Plandemic, and Health Communication. International Journal of Social Media and Online Communities (IJSMOC), 13(1), 1-18. http://doi.org/10.4018/IJSMOC.2021010102

Chicago

Godard, Rebecca, and Susan Holtzman. "COVID-19 Misinformation and Polarization on Twitter: #StayHome, #Plandemic, and Health Communication," International Journal of Social Media and Online Communities (IJSMOC) 13, no.1: 1-18. http://doi.org/10.4018/IJSMOC.2021010102

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Abstract

This study investigated polarization on Twitter related to the COVID-19 pandemic by examining tweets containing #Plandemic (suggests the pandemic is a hoax) or #StayHome (encourages compliance with health recommendations). Over 35,000 tweets from over 25,000 users were collected in April 2020 and examined using sentiment and social network analyses. Compared to #StayHome tweets, #Plandemic tweets came from a more tightly connected network, were higher in negative emotional content, and could be sub-divided into specific categories of misinformation and conspiracy theories. To evaluate the stability of users' COVID-related perspectives, the prevalence of pro- and anti-mask sentiment was measured in same users' tweets approximately four months later. Results revealed substantial stability over time, with 40% of #Plandemic users tweeting anti-mask hashtags compared to just 2% of #StayHome users. Findings demonstrate COVID-related polarization on Twitter and have implications for public health interventions to quell the propagation of misinformation.