Description
In a natural disaster, critical event management can be perceived very differently in terms of disseminating the crisis message via various media including news media, web media, and social media (Ruz et al., 2020). With the wide use of smart devices, social media such as Twitter has become an increasingly valuable platform for sharing real-time urgent news of critical events (Fukui & Ohe, 2020). In contrast to this significant phenomenon of high interactions between organizations and social media users, it has been suggested that scholars should explore more contemporary models and provide some theory-based insights (Speakman & Sharpley, 2012). Existing studies on critical event management mainly focused on communications with the audience via multiple types of media (Lalicic et al., 2020), which only reflects a certain aspect of the information distribution but rarely assesses the efficiency of the platform and network.
This study focused on a 500-year historic flooding in Yellowstone National Park in early June of 2022 due to heavy rains and melting mountain snow. This critical event caused more than 10,000 visitors to be driven out of the park and Yellowstone-related topics arose on Twitter. The present study aims to answer three research questions: First, when does the information flow generated by Twitter users evolve through the critical event management of Yellowstone Park? Second, what are the frequent keywords in the text data and user sentiments? Last, how to identify the most popular, connected, and influential Twitter handles by using social network analysis? To examine the perceptions of Twitter users regarding the flooding event at Yellowstone National Park, all tweets containing the keyword “Yellowstone” were collected from June 9 to June 26, 2022. The specific date range was chosen to include five phases: pre-crisis normality, crisis emergence, crisis occurrence, crisis aftermath, and post-crisis normality. During the study period, the official agent “YellowstoneNPS” posted 46 tweets, and a total of over 181,000 relevant tweets were collected. Based on the five-phase crisis management model, content analysis and sentiment analysis were applied to understand the texts, perceptions, and emotions described in the texts. The keywords identified at different stages during the critical event (e.g., nature, mountains, and old geysers) are more likely to be of people’s interest and could be utilized in digital marketing activities. The sentiment analysis shows that people’s negative emotions dominated the entire period of the critical event, and more efficient interactions between the official agent and influential handles may alleviate people’s anxiety. These findings help better understand the keywords, perceptions, and emotions generated from the texts of the tweets during the Yellowstone flooding. Social network analysis was further employed to examine how information in the tweets related to the Yellowstone flooding is disseminated on the Twitter platform. The results reveal the key influencers along the network and the influential Twitter handles based on their popularity, connectivity, and authority.
These findings thus contribute to the business practice of digital public relations such as cooperating with popular influencers to increase brand awareness. For example, their design of digital marketing needs to consider the strategy of using social media platforms, better engagement with online users, and higher digital impacts on their target audience. This study also provides practical implications for public agencies and organizations regarding the use of social media to reach a wider audience and stakeholders. The paper theoretically contributes to the five-phase crisis management model and helps better understand the distinctions between different phases and their potential influential factors. This study is one of the first attempts to examine the official agent’s efficiency in disseminating crisis information and improving digital public relations during a critical event. It utilized the concept of degree centrality to measure the degree of popularity of a given official agent in the social media network. It also applied betweenness centrality and eigenvector centrality to examine how Twitter handles bridge or interrupt the information flow during a critical event in the social media network, enriching the literature on social media influencers. Notably, these findings provide new evidence of some retweet effects, not only influencing information flow but also creating disinformation during a critical event. It thus extends the existing literature on critical event management and digital public relations.
