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When Everything Is "Nearby": How Airbnb Listings in New York City Exaggerate Proximity (Short Paper)

Authors Mikael Brunila , Priyanka Verma , Grant McKenzie

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Author Details

Mikael Brunila
  • Platial Analysis Lab, Department of Geography, McGill University, Montréal, Canada
  • Urban Politics & Governance Lab, School of Urban Planning, McGill University, Montréal, Canada
Priyanka Verma
  • Platial Analysis Lab, Department of Geography, McGill University, Montréal, Canada
Grant McKenzie
  • Platial Analysis Lab, Department of Geography, McGill University, Montréal, Canada

Funding

  • Brunila, Mikael: Kone Foundation
  • Verma, Priyanka: Social Sciences and Humanities Research Council of Canada

Cite AsGet BibTex

Mikael Brunila, Priyanka Verma, and Grant McKenzie. When Everything Is "Nearby": How Airbnb Listings in New York City Exaggerate Proximity (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 16:1-16:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.GIScience.2023.16

Abstract

In recent years, the emergence and rapid growth of short-term rental (STR) markets has exerted considerable influence on real estate in most large cities across the world. Central location and transit access are two primary factors associated with the prevalence and expansion of STRs, including Airbnbs. Nevertheless, perhaps due to methodological challenges, no research has addressed how location and proximity are represented in the titles and descriptions of STRs. In this paper, we introduce a new methodological pipeline to extract spatial relations from text and show that expressions of distance in STR listings can indeed be quantified and measured against real-world distances. We then comparatively analyze Airbnb reviews (written by guests) and listings (written by hosts) from New York City in order to demonstrate systematically how listings exaggerate proximity compared to reviews. Moreover, we discover spatial patterns to these differences that warrant further investigation.

Subject Classification

ACM Subject Classification
  • Information systems → Geographic information systems
  • Information systems → Information extraction
Keywords
  • spatial proximity
  • distance estimation
  • information extraction
  • named entity recognition
  • short-term rentals

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