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.

Highlights

  • COVID-19 is an infection caused by the novel coronavirus SARS-CoV-2 that is known to cause severe acute respiratory syndrome [1]

  • The time-series analysis demonstrated a strong correlation between the number of tweets posted against mask-wearing and the actual number of COVID-19 new cases, with the volume of negative tweets leading the number of newly reported COVID-19 cases by 9 days

  • The most discussed issues were related to the constitutional rights and the freedom of choice, conspiracy theory, misinformation, health issues, fearmongering, and the ineffectiveness of masks, followed by issues related to mental health, herd immunity, child abuse, and virus-related statistics

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Summary

Introduction

COVID-19 is an infection caused by the novel coronavirus SARS-CoV-2 that is known to cause severe acute respiratory syndrome [1]. The success of initiatives aimed at reopening the national and regional (state) economies relies on public awareness and acceptance of these guidelines for limiting the transmission of COVID-19 Among these guidelines is the importance of 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. These three categories represent almost 65% of the volume of tweets against wearing masks.

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