Robust crisis communication in turbulent times: Conceptualization and empirical evidence from the United States. - Zhong, Wei; Hu, Qian; Kapucu, Naim (Public Administration, 2023)
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. 摘要 本文借鉴稳健性治理的最新相关研究，提出稳健性危机沟通的概念，将其界定为聚焦于满足危机中持续变化的公众沟通需求的动态沟通过程与模式。基于此概念，本文以新型冠状病毒肺炎疫情中的危机沟通为例，构建三维测量方法，用以检验政府危机沟通在内容主题、情感表达和对话互动三方面的稳健程度。本文收集美国50个州长在2020年1月1日至2020年6月30日期间发布的43,642条推特信息，并应用机器学习对所有信息的主题、情感和互动特征进行编码分析。本文发现美国州长危机沟通的稳健性程度总体偏低。美国州长最经常发布与声誉管理相关的推文，其次是政府的疫情防控措施。文章进一步阐释与例证政治因素对州长危机沟通策略的深刻影响，并强调政府部门理解与践行稳健性风险沟通的必要性与重要性。