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Home / Bridging Divides Projects / Theme / Place and Infrastructure / Leveraging Machine Learning to Study Immigrant Renting via Online Advertisements in Vancouver

Leveraging Machine Learning to Study Immigrant Renting via Online Advertisements in Vancouver

Project Overview

Mirroring global trends, a growing share of immigrants to Canada are renting, but the evidence landscape on immigrant renting is patchy at best. In general, rental markets present unique research challenges, making it difficult to get an accurate reading of rental housing activity. Recent studies have leveraged online rental listings for new insights, but the vast majority consider dominant-language platforms only. In places with substantial immigrant communities, such as many Canadian cities, this narrow focus is highly problematic. To address this gap, Harten will examine Vancouver’s rental market using online listings from two platforms: one English, and one Chinese.


Research Questions

  • Does information supply differ across platforms, and to the extent that it does, how do differences online compare to actual settlement patterns?
  • Do listings on the Chinese language platform cater to recent immigrants to Canada?

Methods

  • Computational Methods (Deep Learning)
  • Qualitative Content Analysis
  • Quantitative Text Analysis
  • Statistical Analysis
  • Geospatial Analysis

Collaborators

UBC Centre for Migration Studies

  • Principal Investigator: Julia Harten (Assistant Professor, School of Community and Regional Planning)

Outputs

Work in progress.


Project Status

This project is currently in the Data Analysis phase.

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This research was undertaken thanks in part to funding from the Canada First Research Excellence Fund.

Centre for Migration Studies
Faculty of Arts
1234 Street
Vancouver, BC Canada V0V 0V0
   
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