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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.

This article provides an objective, systematic, and integrated review of the Western academic literature on adventure tourism to discover the theoretical foundations and key themes underlying the field by combining three complementary approaches of bibliometric analysis, content analysis, and a quantitative systematic review. A total of 114 publications on adventure tourism were identified that revealed three broad areas of foci with adventure tourism research: (1) adventure tourism experience, (2) destination planning and development, and (3) adventure tourism operators. Adventure tourism has an intellectual tradition from multiple disciplines, such as the social psychology of sport and recreation. There is an underrepresentation of studies examining non-Western tourists in their own geographic contexts or non-Western tourists in Western geographic contexts. Our findings pave ways for developing a more robust framework and holistic understanding of the adventure tourism field.

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Using the sharing economy (SE) as the context, this article provides a coherent and nuanced methodological understanding of automated content analysis (ACA) in tourism and hospitality (TH) field. By adopting a comparative automated content analysis approach, the paper compares the current TH Western academic literature of the SE with news media discourse in tourism and hospitality from the period 2011-2016 (August) (inclusive). The emerging issues from the news media discourse, such as mobility, SE companies and the role of government are absent in current tourism academic research. Findings reveal that ACA can facilitate a more systematic comparison between different sources of data. This paper offers a starting point for tourism scholars to methodologically engage with ACA that can draw useful insights on a particular context.

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