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01.12.2019 | Regular article | Ausgabe 1/2019 Open Access

EPJ Data Science 1/2019

Inside 50,000 living rooms: an assessment of global residential ornamentation using transfer learning

Zeitschrift:
EPJ Data Science > Ausgabe 1/2019
Autoren:
Xi Liu, Clio Andris, Zixuan Huang, Sohrab Rahimi
Wichtige Hinweise

Electronic Supplementary Material

The online version of this article (https://​doi.​org/​10.​1140/​epjds/​s13688-019-0182-z) contains supplementary material.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abstract

The global community decorates their homes based on personal decisions and contextual influences of their larger cultural and economic surroundings. The extent to which spatial patterns emerge in residential decoration practices has been traditionally difficult to ascertain due to the private nature of interior home spaces. Yet, measuring these patterns can reveal the presence of geographic culture hearths and/or globalization trends.
In this work, we collected over one million geolocated images of interior living spaces from a popular home rental website, Airbnb (http://​airbnb.​com), and used transfer learning techniques to automatically detect the presence of key stylistic objects: plants, books, decor, wall art and predominance of vibrant colors. We investigated patterns of home decor practices for 107 cities on six continents, and performed a deep dive into six major U.S. cities.
We found that world regions show statistically significant variation in decorative element prevalence, indicating differences in geographic cultural trends. At the U.S. neighborhood level, elements were only weakly spatially clustered and found to not correlate with socio-economic neighborhood variables such as income, unemployment rates, education attainment, residential property value, and racial diversity. These results may suggest that American residents in different socio-economic environments put similar effort into personalizing and caring for their homes. More broadly, our results represent a new view of worldwide human behavior and a new application of machine learning techniques to the exploration of cultural phenomena.

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Zusatzmaterial
Supplementary information. (PDF 6.9 MB)
13688_2019_182_MOESM1_ESM.pdf
Multi-page .csv of all 107 cities and element counts. Table of all global cities with average rates of decor prevalence for each indicator. (CSV 7 kB)
13688_2019_182_MOESM2_ESM.csv
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