Constructing and Communicating Covid-19 Stigma on Twitter

A Content Analysis of Tweets during the Early Stage of the Covid-19 Outbreak

Dados Bibliográficos

ID15485077
AutoresYachao Li (0000-0001-8268-1935, College of New Jersey, autor correspondente), Sylvia Twersky (0000-0001-6261-898X, College of New Jersey), Kelsey Ignace (College of New Jersey), Mei Zhao (0000-0003-4218-463X, College of New Jersey), Radhika Purandare (0000-0002-9803-7711, College of New Jersey), Breeda Bennett-Jones (College of New Jersey), Scott R Weaver (0000-0003-3155-4041, Georgia State University)
Ano2020
Volume17
Fascículo18
Páginas6847-6847
Data de publicação2020-09-19
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoInternational Journal of Environmental Research and Public Health (JOURNAL)
Identificadores do periódicoISSN: 1661-7827 • E-ISSN: 1660-4601
EditoraMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph17186847
PMID32961702
OpenAlexW3087651048
IdiomaEN
Citações recebidas24
Referências citadas26

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

Content analysis · Coronavirus disease 2019 (COVID-19 · Disease · Infectious disease (medical specialty · Internet privacy · Misinformation · Political science · Psychiatry · Public health · Social media · Social science · Sociology · Stigma (botany · Computer Science · Hate Speech and Cyberbullying Detection · Medicine · Misinformation and Its Impacts · Nursing · Psychology · Social Psychology · Vaccine Coverage and Hesitancy