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

机译:揭示行业挑战和对Covid-19的商业响应:文本挖掘方法

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PurposeThis study aims to conduct a "real-time" investigation with user-generated content on Twitter to reveal industry challenges and business responses to the coronavirus (Covid-19) pandemic. Specifically, using the hospitality industry as an example, the study analyses how Covid-19 has impacted the industry, what are the challenges and how the industry has responded.Design/methodology/approachWith 94,340 tweets collected between October 2019 and May 2020 by a programmed Web scraper, unsupervised machine learning approaches such as structural topic modelling are applied.Originality/valueThis study contributes to the literature on business response during crises providing for the first time a study of using unstructured content on social media for industry-level analysis in the hospitality context.
机译:目的研究旨在通过推特上的用户生成的内容进行“实时”调查,以揭示对冠状病毒(Covid-19)大流行的行业挑战和业务反应。 具体而言,使用招待业行业作为一个例子,研究分析了Covid-19如何影响行业,挑战以及行业的挑战是什么,以及如何回应.Design/Methodology/Apprachwith 2019年10月和5月2020年间计划的94,340次推文 应用Web刮刀,无监督的机器学习方法,如结构主题建模。更多的危机研究有助于在危机期间对商业响应的文献提供促使在招待中使用非结构化内容对社交媒体的使用非结构化内容进行热情款待的研究 语境。

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