Articlegold2023

Evolving Face Mask Guidance During a Pandemic and Potential Harm to Public Perception: Infodemiology Study of Sentiment and Emotion on Twitter

Divya Ramjee · Catherine C. Pollack · Marie‐Laure Charpignon · Shagun Gupta · Jessica Malaty Rivera · Ghinwa Y. El Hayek +3 more

11 citations0/0 files storedJournal of Medical Internet Research

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Communication and COVID-19 Impact Misinformation and Its Impacts Sentiment Analysis and Opinion Mining

Abstract

BACKGROUND: Throughout the COVID-19 pandemic, US Centers for Disease Control and Prevention policies on face mask use fluctuated. Understanding how public health communications evolve around key policy decisions may inform future decisions on preventative measures by aiding the design of communication strategies (eg, wording, timing, and channel) that ensure rapid dissemination and maximize both widespread adoption and sustained adherence. OBJECTIVE: We aimed to assess how sentiment on masks evolved surrounding 2 changes to mask guidelines: (1) the recommendation for mask use on April 3, 2020, and (2) the relaxation of mask use on May 13, 2021. METHODS: We applied an interrupted time series method to US Twitter data surrounding each guideline change. Outcomes were changes in the (1) proportion of positive, negative, and neutral tweets and (2) number of words within a tweet tagged with a given emotion (eg, trust). Results were compared to COVID-19 Twitter data without mask keywords for the same period. RESULTS: There were fewer neutral mask-related tweets in 2020 (β=-3.94 percentage points, 95% CI -4.68 to -3.21; P<.001) and 2021 (β=-8.74, 95% CI -9.31 to -8.17; P<.001). Following the April 3 recommendation (β=.51, 95% CI .43-.59; P<.001) and May 13 relaxation (β=3.43, 95% CI 1.61-5.26; P<.001), the percent of negative mask-related tweets increased. The quantity of trust-related terms decreased following the policy change on April 3 (β=-.004, 95% CI -.004 to -.003; P<.001) and May 13 (β=-.001, 95% CI -.002 to 0; P=.008). CONCLUSIONS: The US Twitter population responded negatively and with less trust following guideline shifts related to masking, regardless of whether the guidelines recommended or relaxed mask usage. Federal agencies should ensure that changes in public health recommendations are communicated concisely and rapidly.

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2020The COVID-19 social media infodemic 2000Political Trust and Trustworthiness 2019Science audiences, misinformation, and fake news 2017See Something, Say Something: Correction of Global Health Misinformation on Social Media 2017Using Expert Sources to Correct Health Misinformation in Social Media 2020Leveraging media and health communication strategies to overcome the COVID-19 infodemic 2010Handbook of Risk and Crisis Communication 2017Fifteen years of social media in emergencies: A retrospective review and future directions for crisis Informatics

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