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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.07639 |
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| _version_ | 1866912638199398400 |
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| author | Aghaebe, Favour Yahdii Foley, Dustin Atwell, Eric Clark, Stephen |
| author_facet | Aghaebe, Favour Yahdii Foley, Dustin Atwell, Eric Clark, Stephen |
| contents | This study advocates for employing clustering techniques to classify vacation rental properties active during the Covid pandemic to identify inherent patterns and behaviours. The dataset, a collaboration between the ESRC funded Consumer Data Research Centre (CDRC) and AirDNA, encompasses data for over a million properties and hosts. Utilising K-means and K-medoids clustering techniques, we identify homogenous groups and their common characteristics. Our findings enhance comprehension of the intricacies of vacation rental evaluations and could potentially be utilised in the creation of targeted, cluster-specific policies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_07639 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Property Classification of Vacation Rental Properties during Covid-19 Aghaebe, Favour Yahdii Foley, Dustin Atwell, Eric Clark, Stephen Machine Learning This study advocates for employing clustering techniques to classify vacation rental properties active during the Covid pandemic to identify inherent patterns and behaviours. The dataset, a collaboration between the ESRC funded Consumer Data Research Centre (CDRC) and AirDNA, encompasses data for over a million properties and hosts. Utilising K-means and K-medoids clustering techniques, we identify homogenous groups and their common characteristics. Our findings enhance comprehension of the intricacies of vacation rental evaluations and could potentially be utilised in the creation of targeted, cluster-specific policies. |
| title | Property Classification of Vacation Rental Properties during Covid-19 |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2510.07639 |