Applications of Machine Learning to Airbnb: Impact of Cleanliness on Listings
By: Sean Larkin, Max Koch, and Nguyen Bao Lam
Advisor: Dr. Lily Shen & Sean Wilkoff
Abstract
- After COVID-19 struck, there has become a ‘new normal’ for cleanliness standards across all industries.
- This led us to question: How do renters value ‘cleanliness’ in the real estate market?
- We investigated the relationship between listing prices & bookings and the level of COVID-19 cases at a county level in the Austin, Texas area.
- We utilized machine learning, multiple linear regression models, & critical thinking to evaluate this question
- Concluded that renters DO value rental cleanliness
Why Austin?
Listing Cleanliness
Machine Learning
Creating The Index
Austin Summary Statistics
Key Takeaways:
- 228,348 Airbnb Listing observations in Austin, Texas
- Only 35% of Listings include ‘Clean’ in description
- As of July 22, 2020:
- 8822 COVID-19 Cases in Travis County
- 186,436 COVID-19 cases in Texas State
- Generated Variables
- COVID-19 Period
- Monthly Bookings
- Average Nightly Price
- Monthly Income
Multiple Linear Regression Model
| Variables | Monthly Bookings | Nightly Price | Monthly Income |
| COVID-19 Period | -0.162*** | -6.213** | -164.783*** |
| Description Cleanliness Score | 0.368*** | -0.576 | 79.840* |
| Review Cleanliness Score | 2.393*** | 16.257*** | 920.745*** |
| COVID Description Interaction | 0.466*** | -2.226 | 126.025*** |
| Review COVID Interaction | 1.151*** | -12.616*** | 320.311*** |
| Review Description Interaction | 0.586*** | -8.526*** | 61.406 |
| Review Description COVID Interaction | -0.354 | 4.581 | -57.770 |
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- Clean units should expect to see an additional $446.336 in monthly income after COVID-19
- Clean units should also expect to see a 1.615 increase in bookings per month after COVID-19
- We did not find any evidence of hosts increasing price for clean units
