Accommodation Descriptions that Influence Airbnb Occupancy Rate Using Ontology-Reference-Cited by-同舟云学术

Accommodation Descriptions that Influence Airbnb Occupancy Rate Using Ontology

Published:2023 Issue: Volume: Page:121-130
ISSN:2367-3370
Container-title:Proceedings of the 19th International Conference on Computing and Information Technology (IC2IT 2023)
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Author:

Choogortoud Rattapon^ORCID,Muntham Dittapol^ORCID,Chuethong Worawek^ORCID,Srisoontorn Sart^ORCID,limpaporn Orasa^ORCID,Utakrit Nathaporn^ORCID,Viriyapant Kanchana^ORCID,Bhumpenpein Nalinpat^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-30474-3_11

Reference12 articles.

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2. Richard, D.M., Anthony, C., Tiffany, K., Lena, T., Nour, A.Z.A.M.: The Impact of an AirBnb host’s listing description sentiment and length on occupancy rates. arXiv:1711.09196, 1–17, November (2017). https://doi.org/10.48550/arXiv.1711.09196

3. Lanfei, G., Hui, L., Sai, L., Jingjing, Y., Rob, L.: How does constraining description affect guest booking decisions and satisfaction?. Tourism Manage. 93, 104607 (2022). https://doi.org/10.1016/j.tourman.2022.104607

4. Muhammad, R.R., Walayat, H., Asaf. V.: Performance analysis of deep approaches on airbnb sentiment reviews. In: the 10th International Symposium on Digital Forensics and Security (ISDFS) (2022)

5. Md DI, Bin L, Kazi SI, Rakibul A, Md RM, Md EH (2022) Airbnb rental price modeling based on latent Dirichlet Allocation and MESF-XGBoost composite model. Mach. Learn. Appl. 7:1–9. https://doi.org/10.1016/j.mlwa.2021.100208