Using Latent Dirichlet Allocation to investigate guest experience in Airbnb accommodation during COVID-19 pandemic in the United Kingdom

Abstract

The sharing economy in the accommodation business provides the alternatives for travelers, while this market segment is growing significantly. It is important to understand the requirement of the guests' experience in order to provide the better service comparing to the traditional accommodation services, especially during the pandemic crisis of Covid-19 when tourism industry was frozen globally. The current study explores the reviews on Airbnb platform by employing the Latent Dirichlet Allocation technique in order to understand the experiences among Airbnb guests during the Covid-19 crisis. The results revealed that several latent topics from previous studies were discovered, such as accommodation, location, neighborhood, accessibility, amenities, etc., with some unique topics that can be suggested to the existing knowledge. The theoretical and practical contributions in both tourism and the analysis technique contexts were discussed.