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In JMIR public health and surveillance

BACKGROUND : Despite the presence of scientific evidences supporting the importance of wearing masks to curtail the widespread of the COVID-19 virus, wearing masks has stirred up a significant debate particularly on social media.

OBJECTIVE : To investigate the topics associated with the public discourse against wearing masks in the United States. Further, we studied the relationship between the anti-mask discourse on social media and the number of new COVID-19 cases.

METHODS : Using hashtags against wearing masks, we collected a total of 51,170 English tweets between January 1st, 2020 and October 27th, 2020. We used machine learning techniques to analyze the data collected. We investigated the relationship between the volume of tweets that are against mask-wearing and the daily volume of new COVID-19 cases using the Pearson Correlation between the two-time series.

RESULTS : The results and analysis showed that social media could help identify important insights related to wearing masks. The results of topic mining identified 10 categories/themes of user concerns dominated by 1) constitutional rights and freedom of choice followed by 2) conspiracy theory, population control and big pharma, and 3) Fake news, fake numbers, fake pandemic. Combined, these three categories represent almost 65% of the volume of tweets against masks. The relationship between the volume of tweets against wearing masks and the reported new COVID-19 cases depicted a strong correlation where the rise in the volume of negative tweets is leading the rise in the number of new cases by nine days.

CONCLUSIONS : The 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 like 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.


Al-Ramahi Mohammad, Elnoshokaty Ahmed, El-Gayar Omar, Nasralah Tareq, Wahbeh Abdullah