Research article Topical Sections

Rapid assessment of communication consistency: sentiment analysis of public health briefings during the COVID-19 pandemic

  • Received: 27 December 2021 Revised: 21 January 2022 Accepted: 25 January 2022 Published: 10 February 2022
  • Background

    A key component of the initial public health response to the COVID-19 pandemic involved the use of mass media briefings led by public health officials to communicate updates during a time of great uncertainty and rapidly changing information. This study aims to examine the consistency of communications expressed during the public health briefings to generate novel insights about the type, direction, and strength of public health messages. The data source included 131 readily accessible public health briefings alongside the provincial and national new confirmed case counts during the first two waves of rapidly increasing cases during the pandemic in Alberta, Canada. We employed sentiment analysis as a text mining technique to explore the types and frequency of words in public health briefings conveying positive and negative sentiments. Using statistical analyses and data visualizations, we examined how public health messaging shifted with case trends.

    Results

    Our findings indicate consistent public health messaging in terms of sentiments regardless of case count fluctuations, an association of specific words with conveying positive and negative sentiments, and a focus on particular message patterns at different points during the first two waves of the COVID-19 pandemic.

    Conclusion

    Our findings demonstrate the practical implications and methodological advantages of using sentiment analysis as a data analytics tool for rapidly and objectively assessing the consistency of health communications during a public health crisis.

    Citation: Okan Bulut, Cheryl N. Poth. Rapid assessment of communication consistency: sentiment analysis of public health briefings during the COVID-19 pandemic[J]. AIMS Public Health, 2022, 9(2): 293-306. doi: 10.3934/publichealth.2022020

    Related Papers:

  • Background

    A key component of the initial public health response to the COVID-19 pandemic involved the use of mass media briefings led by public health officials to communicate updates during a time of great uncertainty and rapidly changing information. This study aims to examine the consistency of communications expressed during the public health briefings to generate novel insights about the type, direction, and strength of public health messages. The data source included 131 readily accessible public health briefings alongside the provincial and national new confirmed case counts during the first two waves of rapidly increasing cases during the pandemic in Alberta, Canada. We employed sentiment analysis as a text mining technique to explore the types and frequency of words in public health briefings conveying positive and negative sentiments. Using statistical analyses and data visualizations, we examined how public health messaging shifted with case trends.

    Results

    Our findings indicate consistent public health messaging in terms of sentiments regardless of case count fluctuations, an association of specific words with conveying positive and negative sentiments, and a focus on particular message patterns at different points during the first two waves of the COVID-19 pandemic.

    Conclusion

    Our findings demonstrate the practical implications and methodological advantages of using sentiment analysis as a data analytics tool for rapidly and objectively assessing the consistency of health communications during a public health crisis.



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    Acknowledgments



    The research leading to these results received funding from the University of Alberta's Endowment Fund for the Support for the Advancement of Scholarship (SAS) Program. The authors would like to thank Adrienne Montgomerie who provided feedback and editing advice.

    Conflict of interest



    The authors declare no conflict of interest.

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