Robust crisis communication in turbulent times: Conceptualization and empirical evidence from the United States
By: Zhong, Wei Hu, Qian and Kapucu, Naim
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Material type: 
BookPublisher: Public Administration: An International Quarterly Description: 10(1), Mar, 2023: p.158-181.
In:
Public Administration: An International QuarterlySummary: Drawing on recent research on robust governance, we conceptualize robust crisis communication as a dynamic process centered on evolving public communication demands. We propose a three-dimensional measurement for empirically examining the robustness of government crisis communication in the context of the COVID-19 pandemic. We collected 43,642 Twitter messages posted by 50 state governors in the United States from January 1 to June 30, 2020. We applied machine learning algorithms to code the voluminous Twitter data based on messaging topics, sentiments, and interactions. This study found an overall low level of robustness in the governors' crisis communication. Governors most frequently posted reputation management tweets, followed by tweets about the government's handling of the pandemic. This research presents empirical evidence for the heavy influence of politics on governors' crisis communication strategies and highlights the need to understand and build robust crisis communication. – Reproduced
https://onlinelibrary.wiley.com/doi/10.1111/padm.12855
| Item type | Current location | Call number | Vol info | Status | Date due | Barcode |
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Articles
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Indian Institute of Public Administration | 10(1), Mar, 2023: p.158-181 | Available | AR130219 |
Drawing on recent research on robust governance, we conceptualize robust crisis communication as a dynamic process centered on evolving public communication demands. We propose a three-dimensional measurement for empirically examining the robustness of government crisis communication in the context of the COVID-19 pandemic. We collected 43,642 Twitter messages posted by 50 state governors in the United States from January 1 to June 30, 2020. We applied machine learning algorithms to code the voluminous Twitter data based on messaging topics, sentiments, and interactions. This study found an overall low level of robustness in the governors' crisis communication. Governors most frequently posted reputation management tweets, followed by tweets about the government's handling of the pandemic. This research presents empirical evidence for the heavy influence of politics on governors' crisis communication strategies and highlights the need to understand and build robust crisis communication. – Reproduced
https://onlinelibrary.wiley.com/doi/10.1111/padm.12855
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