Risk perception and crisis communication during the Covid-19 pandemic: Analysis based on Twitter hashtags

Abstract

This research evaluates response strategies to crisis communication, in terms of perceived risks, in organizations during the Covid-19 pandemic by studying the main discussion topics in social media. The data was collected from Twitter between March and April 2020. By using big data software, a total number of 3559255 tweets in different languages were extracted worldwide from Twitter API of popular hashtags on the Covid-19 pandemic. The data processing was carried out through the association of terms in order to identify patterns and relationships in the discussion topics. The results indicate that the relationships of the terms "crisis" and "risks" were statistically significant with seven important topics for businesses, users, and consumers: "business", "economic and financial", "social"," health"," work"," family" and "government"; and in turn these seven topics are related to other terms related to the impact of the crisis, the response to the crisis, aid, the watch out, and support. This research has implications for the situational crisis communication theory by showing that in situations with high perceived risk, such as the Covid-19 pandemic crisis, the use of crisis response strategies predominates in organizations. This research also has implications for managers who can use crisis response strategies to rebuild their reputation and avoid market losses, thus helping to reduce the effects of unpredictable crisis situations.

Analysis of sentiment in the European Central Bank’s social media activity during the Covid-19 pandemic and Ukraine War: A navigating crisis communication

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Topics and feelings of entrepreneurs during a crisis period: Analysis of business Twitter hashtags

“…Identifying the relationships between terms when they appear together is possible through the association mining technique (Correia et al, 2018;Carvache et al, 2022). When analyzing terms and hashtags, relevant topics and words for companies are located since the associations of localized words can be revealed in trends or constructs that, in an exploratory analysis, allow testing hypotheses and detecting relationships between constructs (Harlow & Oswald, 2016).…”