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Cited by 480

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

What do Airbnb users care about? An analysis of online review comments

Open access
Cheng, Mingming, Jin, Xin·2019·International Journal of Hospitality Management

Abstract

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.

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Registry

Crossref · 10.1016/j.ijhm.2018.04.004

Cites

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Metadata

Authors
Cheng, M., & Jin, X.
Venue
International Journal of Hospitality Management
Publisher
Elsevier BV
Published
2019-01
Volume
76
Pages
58-70
ISSN
0278-4319 (ISSN-L)
OpenAlex
W2811422155
Cited by
480
References
6
FWCI
92.82
Type
journal article
Language
en
Open access
bronze

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.