۱- Introduction

۲- Literature review

۳- Research design

۴- Findings

۵- Discussion and implications

References

Abstract

This study investigates the attributes that influence Airbnb users’ experiences by analysing a “big data” set of online review comments through the process of text mining and sentiment analysis. Findings reveal that Airbnb users tend to evaluate their experience based on a frame of reference derived from past hotel stays. Three key attributes identified in the data include ‘location’, ‘amenities’ and ‘host’. Surprisingly, ‘price’ is not identified as a key influencer. The analysis suggests a positivity bias in Airbnb users’ comments while negative sentiments are mostly caused by ‘noise’. This research offers an alternative approach and more coherent understanding of the Airbnb experience. Methodologically, it contributes by illustrating how big data can be used and visually interpreted in tourism and hospitality studies.

Introduction

The sharing economy phenomenon is driven by people’s desire for sustainability, enjoyment of the activity and economic gains (Hamari et al., 2015), which has sparked mounting interest from researchers and business. The sharing economy has enabled people to engage in selling services through reputable online platforms such as Uber or Airbnb. The focus of this article is on Airbnb, a peer-to-peer internet platform provider that has become one of the most successful models in the sharing economy. Airbnb has gained rapid popularity among its users across the world. Since its establishment in San Francisco in 2008, it has experienced rapid growth connecting a total number of more than 200 million guests across more than 65,000 cities (Airbnb, 2017). Its rapid growth has changed the way the business community have come to view it (Cheng, 2016). Arguably, Airbnb disrupted the whole established hotel system with an estimated value of $30 billion, which is ahead of most hospitality groups (Skift, 2016). Some analysts estimate that in the next five years, Airbnb will rack up half a billion “room nights” per year with the potential to grow to a full billion annually by 2025 (Verhage, 2016). Given its popularity and reach in the tourism and hospitality industry, researchers have begun undertaking systematic studies on the Airbnb phenomenon, shifting from a media portrayed paradigm to a research driven agenda. Existing research has examined Airbnb’s potential disruption to the established accommodation sector (Guttentag, 2015), price strategies (Wang and Nicolau, 2017), advertising appeals (Liu and Mattila, 2017), potential discrimination (Edelman et al., 2016), impact on labour (Fang et al., 2016), and Airbnb user behaviour and experiences (Tussyadiah, 2016). A key attribute of the Airbnb user experience is its ability to offer an authentic tourist-host encounter that cannot be replicated in conventional hotels (Tussyadiah, 2016).