The COVID-19 pandemic and the lockdown bore a devastating impact on organizations across the globe. In this crisis, organizations belonged to the victim cluster, with a low crisis responsibility. Nevertheless, organizations needed to strategize their crisis responses and communicate with stakeholders to reduce the threat to reputational capital and manage stakeholder reactions in the pandemic. In this paper, we studied organizational Twitter communication during the COVID-19 crisis through the lens of the situational crisis communication theory (SCCT). We analyzed 325,627 tweets collected from the Twitter pages of 464 organizations belonging to the Fortune 500 list. The Twitter data reflected organizational COVID-19 crisis response strategies and demonstrated organizational use of Twitter for crisis communication. We applied lexicon-based emotion mining to identify and measure emotions, and topic mining to measure crisis response topic scores from this large multi-organization dataset. We performed path analysis to test our research model derived from the SCCT. The analysis showed that instructing and adjusting information can minimize threats to organizational reputation in a victim crisis and manage stakeholder reactions. Positive emotions showed a stronger association with behavioral outcomes. Emotion neutral tweets generated more favorable stakeholder reactions. The paper contributes to the literature on situational crisis communication for a victim crisis. The multi-organization data addresses the sensitive inter-organization dependencies and improves the understanding of crisis communication. It provides practitioners an insight into the effect of the COVID-19 crisis response strategies on stakeholder emotions and behavior.

COVID-19 大流行和封锁对全球组织造成了毁灭性影响。在这场危机中，组织属于受害者群，危机责任较低。然而，组织需要制定危机应对策略并与利益相关者进行沟通，以减少对声誉资本的威胁并管理利益相关者在大流行中的反应。在本文中，我们通过情境危机传播理论 (SCCT) 的视角研究了 COVID-19 危机期间的组织 Twitter 传播。我们分析了从属于财富 500 强名单的 464 个组织的 Twitter 页面收集的 325,627 条推文。Twitter 数据反映了组织的 COVID-19 危机应对策略，并展示了组织使用 Twitter 进行危机沟通的情况。我们应用基于词典的情绪挖掘来识别和测量情绪，并应用主题挖掘来测量来自这个大型多组织数据集的危机响应主题分数。我们进行了路径分析以测试我们源自 SCCT 的研究模型。分析表明，指导和调整信息可以最大限度地减少受害者危机中对组织声誉的威胁，并管理利益相关者的反应。积极情绪与行为结果有更强的关联。情绪中性的推文产生了更有利的利益相关者反应。本文为受害者危机的情境危机沟通文献做出了贡献。多组织数据解决了敏感的组织间依赖关系，并提高了对危机沟通的理解。