Airbnb Occupancy Rate Influential Detection Based on Hosting Descriptions with LDA
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-30474-3_9
Reference9 articles.
1. Bessadeg F (2022) The world’s most visited cities. https://travelness.com/most-visited-cities-in-the-world. Accessed 25 Oct 2022
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3. Muhammad RR, Walayat H, Asaf V (2022) Performance analysis of deep approaches on airbnb sentiment reviews. In: 2022 10th International symposium on digital forensics and security (ISDFS), 2022. https://doi.org/10.1109/ISDFS55398.2022.9800816
4. Mohamed C, Omar B, Younes C (2021) Towards a machine learning and data mining approach to identify customer satisfaction factors on Airbnb. In: 2021 7th International conference on optimization and applications (ICOA), 2021. https://doi.org/10.1109/ICOA51614.2021.9442657
5. Daniel G (2019) Progress on Airbnb: a literature review. J Hosp Tour Technol 10(4):814–844. https://doi.org/10.1108/JHTT-08-2018-0075
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