Revealing industry challenge and business response to Covid-19: a text mining approach

Purpose This study aims to conduct a “real-time” investigation with user-generated content on Twitter reveal industry challenges and business responses the coronavirus (Covid-19) pandemic. Specifically, using hospitality as an example, analyses how Covid-19 has impacted industry, what are responded. Design/methodology/approach With 94,340 tweets collected between October 2019 May 2020 by programmed Web scraper, unsupervised machine learning approaches such structural topic modelling applied. Originality/value contributes literature response during crises providing for first time of unstructured social media industry-level analysis in context.