Authors:
Iván Ruiz-Rube
1
;
Inmaculada Arnedillo-Sánchez
2
and
Antonio Balderas
1
Affiliations:
1
School of Engineering, University of Cádiz, Spain
;
2
School of Computer Science and Statistics, Trinity College Dublin, Ireland
Keyword(s):
Accommodation Rental Platforms, Machine Learning, Web Scraping, Search Engines.
Abstract:
The global irruption of ‘shared-accommodation platforms’ has ignited debate regarding the implications of the unprecedented growth of the short-term rental market. While some argue that they have generated new business, work and wealth others, highlight their wider societal, economic and legal effects. Short-term rental removes long-term housing from the market, forces rent prices up, saturates areas with tourism, generates safety and liability concerns and by and large, it is awash with likely illegal listings. This paper presents MISTRuST (accoMmodatIon Short Term Rental Scanning Tool) a computational intelligence based system aimed at uncovering whether a property is being listed in short-term rental (STR) platforms. It enables users to monitor property by scheduling automatic searches and checking listings returned by the system against the target property. The asynchronous pipeline architecture involves three stages: data ingestion, data enrichment and data matching. Preliminary
test results with a set of listings are encouraging. However, further evaluation is needed to improve the accuracy of the system on a larger scale. It is hoped MISTRuST will help stakeholders such as property owners, state and agencies and others tackle the growing concern over unlawful STRs and contribute towards sustainable solutions.
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