The aim of this paper is to demonstrate how text mining of online reviews can support business continuity management in the sharing economy during market turbulence. We use topic modelling and sentiment analysis of Airbnb online reviews to identify specific areas where short-term rental hosts can harness the power of the sharing-economy business model to bounce back from market disruption. The dataset comprises 894,686 online Airbnb reviews from the pre- and post-Covid periods. We approach the pandemic as a paradigm example of a high-impact, external market shock and infer insights and recommendations from the dataset that are relevant to the general understanding of business continuity management in the short-term rental, peer-to-peer sharing economy.

中文翻译：

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共享经济中的业务连续性管理：来自 Airbnb 在线评论的见解


本文的目的是展示在线评论的文本挖掘如何在市场动荡期间支持共享经济中的业务连续性管理。我们对 Airbnb 在线评价进行主题建模和情感分析，以确定短租房东可以利用共享经济商业模式的力量从市场动荡中恢复过来的具体领域。该数据集包括 894,686 条在线 Airbnb 评论，这些评论来自 Covid 前后。我们将大流行视为高影响的外部市场冲击的范例，并从数据集中推断出与短期租赁、点对点共享经济中业务连续性管理的一般理解相关的见解和建议。