Identification of the Breach of Short-term Rental Regulations in Irish Rent Pressure Zones

TL;DR

This paper presents a novel method using neural networks and geospatial analysis to identify potential breaches of short-term rental regulations in Irish Rent Pressure Zones, addressing data limitations and aiming to support regulatory enforcement.

Contribution

It introduces a breach detection framework combining Residual and Siamese Neural Networks with geospatial algorithms to identify unpermitted short-term rentals using publicly available data.

Findings

The model can filter outdoor images to improve accuracy.

It compares indoor photos to identify multiple listings of the same property.

Occupancy estimation combined with sentiment analysis offers a reasonable breach likelihood estimate.

Abstract

The housing crisis in Ireland has rapidly grown in recent years. To make a more significant profit, many landlords are no longer renting out their houses under long-term tenancies but under short-term tenancies. The shift from long-term to short-term rentals has harmed the supply of private housing rentals. Regulating rentals in Rent Pressure Zones with the highest and rising rents is becoming a tricky issue. In this paper, we develop a breach identifier to check short-term rentals located in Rent Pressure Zones with potential breaches only using publicly available data from Airbnb (an online marketplace focused on short-term home-stays). First, we use a Residual Neural Network to filter out outdoor landscape photos that negatively impact identifying whether an owner has multiple rentals in a Rent Pressure Zone. Second, a Siamese Neural Network is used to compare the similarity of indoor photos to determine if multiple rental posts correspond to the same residence. Next, we use the Haversine algorithm to locate short-term rentals within a circle centered on the coordinate of a permit. Short-term rentals with a permit will not be restricted. Finally, we improve the occupancy estimation model combined with sentiment analysis, which may provide higher accuracy. Because Airbnb does not disclose accurate house coordinates and occupancy data, it is impossible to verify the accuracy of our breach identifier. The accuracy of the occupancy estimator cannot be verified either. It only provides an estimate within a reasonable range. Users should be skeptical of short-term rentals that are flagged as possible breaches.