What do Airbnb users care about? An analysis of online review comments
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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.
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Volgger, Michael; Pforr, Christof; Stawinoga, A.; Taplin, Ross; Matthews, S. (2018)Airbnb is the most prominent example of novel peer-to-peer networks in tourism. This new form of accommodation provision may alter demand structures in tourism destinations and has led to uncertainty amongst established ...
Cheng, Mingming; Zhang, G. (2019)As the number of Chinese tourists using Airbnb for their holiday accommodation is steadily increasing, this study investigates western Airbnb hosts' experiences with Chinese outbound tourists. In an analysis of hosts' ...
Volgger, Michael; Pforr, C.; Reiser, D. (2018)