Journal of Medical Internet Research · 2023 · 10 citations · 38 references
Social SciencesCommunicationPublic Health PracticeHealth CommunicationRisk CommunicationSocial InfluenceCrisis CommunicationHealth Communication PolicyHealth Risk CommunicationSentiment AnalysisSocial MediaSocial Media Health CommunicationBehavioral Change PolicyCovid-19 Vaccination PolicyInterrupted Series AnalysisInterrupted Time Series DesignPreventive Health CommunicationPublic Health Communication MonitoringPublic Perception AssessmentPublic Safety Communications
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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Political Trust and Trustworthiness
Margaret Levi, Laura Stoker · Annual Review of Political Science · 2000 · 2.1K citations
Public Affairs, Political Communication, Political Science +15
From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series
Brendan O’Connor, Ramnath Balasubramanyan, Bryan Routledge et al. · Proceedings of the International AAAI Conference on Web and Social Media · 2010 · 2K citations · Full text
Public Affairs, Political Communication, Political Science +17
The COVID-19 social media infodemic
Scientific Reports · 2020 · 1.6K citations · Full text