Abstract
The objective of this chapter is to present a case of text mining on Airbnb user reviews to analyze and understand various aspects that drive customer satisfaction. The study can be extended further to discover segmentation and targeting of spaces that can take customer satisfaction to the next level and can also consider possibilities of geography specific, travel and purpose specific guest and host requirements. We are trying to gain insights about the challenges faced by customers in sharing economy along with ways to develop “super hosts”. Thus, this work will try to advance our understanding about tourism and hospitality industry by presenting a case of big data analyses on Airbnb user reviews.
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Appendices
Appendices
See Figs. 10.1, 10.2, 10.3, 10.4, 10.5, 10.6, 10.7, 10.8 and 10.9.
Aspects Polarity
Positive Aspects Example set
Negative Aspects Example Set
Positive Aspects graph
Negative Aspects graph
Aspects Stacked
Correlation Matrix
Positive Correlation Sample-Facilities
Negative Correlation Sample-Facilities
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Joseph, G., Varghese, V. (2019). Analyzing Airbnb Customer Experience Feedback Using Text Mining. In: Sigala, M., Rahimi, R., Thelwall, M. (eds) Big Data and Innovation in Tourism, Travel, and Hospitality. Springer, Singapore. https://doi.org/10.1007/978-981-13-6339-9_10
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