ArticleJMIR public health and surveillance2021
Public Discourse Against Masks in the COVID-19 Era: Infodemiology Study of Twitter Data.
Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.
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Who cites it
32 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- When Infodemic Meets Epidemic: Systematic Literature Review.JMIR public health and surveillance · 2025Pooled it
- Masks and respirators for prevention of respiratory infections: a state of the science review.Clinical microbiology reviews · 2024Pooled it
- Comparison of Mask-Wearing Behavior on Social Media and Its Relationship With Demographic Characteristics During the COVID-19 Pandemic: Social Media Data Analysis Between the United States and Japan.JMIR human factors · 2026Article
- Regional and temporal patterns of partisan polarization during the COVID-19 pandemic in the United States and Canada.PloS one · 2026Article
- Themes, Policies, and Attention Shifts Regarding COVID-19 Vaccinations in German-Speaking Regions: Infoveillance Study Using Tweets.Journal of medical Internet research · 2025Article
- Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis.Journal of medical Internet research · 2025Article
- Anti-masking Posts on Instagram: Content Analysis During the COVID-19 Pandemic.Safety and health at work · 2025Article
- Characterizing the interactions between influenza and respiratory syncytial viruses and their implications for epidemic control.Nature communications · 2024Article
- Article
- Dynamic Associations Between Centers for Disease Control and Prevention Social Media Contents and Epidemic Measures During COVID-19: Infoveillance Study.JMIR infodemiology · 2024Article
- Socio-economic pandemic modelling: case of Spain.Scientific reports · 2024Article
- Protection, freedom, stigma: a critical discourse analysis of face masks in the first wave of the COVID-19 pandemic and implications for medical education.Canadian medical education journal · 2023Article
- The (Re-)Emergence and Spread of Viral Zoonotic Disease: A Perfect Storm of Human Ingenuity and Stupidity.Viruses · 2023Article
- Examining thematic and emotional differences across Twitter, Reddit, and YouTube: The case of COVID-19 vaccine side effects.Computers in human behavior · 2023Article
- Barriers to and facilitators of populational adherence to prevention and control measures of COVID-19 and other respiratory infectious diseases: a qualitative evidence synthesis.European respiratory review : an official journal of the European Respiratory Society · 2023Review
- The Relationship Between Face Mask Use and Face-Touching Frequency in Public Areas: Naturalistic Study.Interactive journal of medical research · 2023Article
- Examining Rural and Urban Sentiment Difference in COVID-19-Related Topics on Twitter: Word Embedding-Based Retrospective Study.Journal of medical Internet research · 2023Article
- Scientific Misinformation and Mistrust of COVID-19 Preventive Measures among the UK Population: A Pilot Study.Vaccines · 2023Article
- Article
- MonkeyPox2022Tweets: A Large-Scale Twitter Dataset on the 2022 Monkeypox Outbreak, Findings from Analysis of Tweets, and Open Research Questions.Infectious disease reports · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite scientific evidence supporting the importance of wearing masks to curtail the spread of COVID-19, wearing masks has stirred up a significant debate particularly on social media.
objectiveThis study aimed to investigate the topics associated with the public discourse against wearing masks in the United States. We also studied the relationship between the anti-mask discourse on social media and the number of new COVID-19 cases.
methodsWe collected a total of 51,170 English tweets between January 1, 2020, and October 27, 2020, by searching for hashtags against wearing masks. We used machine learning techniques to analyze the data collected. We investigated the relationship between the volume of tweets against mask-wearing and the daily volume of new COVID-19 cases using a Pearson correlation analysis between the two-time series.
resultsThe results and analysis showed that social media could help identify important insights related to wearing masks. The results of topic mining identified 10 categories or themes of user concerns dominated by (1) constitutional rights and freedom of choice; (2) conspiracy theory, population control, and big pharma; and (3) fake news, fake numbers, and fake pandemic. Altogether, these three categories represent almost 65% of the volume of tweets against wearing masks. The relationship between the volume of tweets against wearing masks and newly reported COVID-19 cases depicted a strong correlation wherein the rise in the volume of negative tweets led the rise in the number of new cases by 9 days.
conclusionsThese findings demonstrated the potential of mining social media for understanding the public discourse about public health issues such as wearing masks during the COVID-19 pandemic. The results emphasized the relationship between the discourse on social media and the potential impact on real events such as changing the course of the pandemic. Policy makers are advised to proactively address public perception and work on shaping this perception through raising awareness, debunking negative sentiments, and prioritizing early policy intervention toward the most prevalent topics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.