Constructing and Communicating COVID-19 Stigma on Twitter: A Content Analysis of Tweets during the Early Stage of the COVID-19 Outbreak

Yachao Li, Sylvia Twersky, Kelsey Ignace, Mei Zhao, Radhika Purandare, Breeda Bennett-Jones and Scott R. Weaver
Additional contact information
Yachao Li: Department of Communication Studies, The College of New Jersey, Ewing, NJ 08628, USA
Sylvia Twersky: Department of Public Health, The College of New Jersey, Ewing, NJ 08628, USA
Kelsey Ignace: Department of Public Health, The College of New Jersey, Ewing, NJ 08628, USA
Mei Zhao: Department of Public Health, The College of New Jersey, Ewing, NJ 08628, USA
Radhika Purandare: Department of Communication Studies, The College of New Jersey, Ewing, NJ 08628, USA
Breeda Bennett-Jones: Department of Communication Studies, The College of New Jersey, Ewing, NJ 08628, USA
Scott R. Weaver: School of Public Health, Georgia State University, Atlanta, GA 30303, USA

IJERPH, 2020, vol. 17, issue 18, 1-12

Abstract: This study focuses on stigma communication about COVID-19 on Twitter in the early stage of the outbreak, given the lack of information and rapid global expansion of new cases during this period. Guided by the model of stigma communication, we examine four types of message content, namely mark, group labeling, responsibility, and peril, that are instrumental in forming stigma beliefs and sharing stigma messages. We also explore whether the presence of misinformation and conspiracy theories in COVID-19-related tweets is associated with the presence of COVID-19 stigma content. A total of 155,353 unique COVID-19-related tweets posted between December 31, 2019, and March 13, 2020, were identified, from which 7000 tweets were randomly selected for manual coding. Results showed that the peril of COVID-19 was mentioned the most often, followed by mark, responsibility, and group labeling content. Tweets with conspiracy theories were more likely to include group labeling and responsibility information, but less likely to mention COVID-19 peril. Public health agencies should be aware of the unintentional stigmatization of COVID-19 in public health messages and the urgency to engage and educate the public about the facts of COVID-19.

Keywords: COVID-19; coronavirus 2019; Twitter; stigma; model of stigma communication; content analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://www.mdpi.com/1660-4601/17/18/6847/pdf (application/pdf)
https://www.mdpi.com/1660-4601/17/18/6847/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:17:y:2020:i:18:p:6847-:d:416022

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().