Public health

Pathology

Sociology

Qualitative research

Disease

Population

Coronavirus disease 2019 (COVID-19)

Social science

Infectious disease (medical specialty)

Pandemic

Internet privacy

World Wide Web

Nursing

Philosophy

Psychology

Narrative

Social media analytics

Popularity

Computer science

Linguistics

Social media

Thematic analysis

Medicine

Social psychology

Environmental health

Vaccines

This study aims to understand public discussions regarding COVID-19 vaccine on Parler, a newer social media platform that recently gained in popularity. Through analyzing a random sample (n = 400) of Parler posts using the hashtags #COVID19Vaccine and #NoCovidVaccine, we use the concept of echo chambers to understand users’ discussions through a text analytics approach. Thematic analysis reveals five key themes: reasons to refuse the COVID-19 vaccine (40%), side effects of the COVID-19 vaccine (28%), population control through the COVID-19 vaccine (23%), children getting vaccinated without parental consent (5%), and comparison of other health issues with COVID-19 (2%). Textual analysis shows that the most frequently used words in the corpus were: nocovidvaccine (348); vaccine (264); covid (184); covid19 (157); and vaccines (128). These findings suggest that users adopted different terms and hashtags to express their beliefs regarding the COVID-19 vaccine. Further, findings revealed that users used certain hashtags such as “echo” to encourage like-minded people to reinforce their existing beliefs on COVID-19 vaccine efficacy and vaccine acceptance. These findings have implications for public health communication in attempts to correct false narratives on social media platforms. Through widely sharing the scientific findings of COVID-19 vaccine-related studies can help individuals understand the COVID-19 vaccines efficacy accurately.

#Scamdemic, #Plandemic, or #Scaredemic: What Parler Social Media Platform Tells Us about COVID-19 Vaccine