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Cited by 26Housing Market and EconomicsStock Market Forecasting MethodsForecasting Techniques and Applications

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Can Web Search Queries Predict Prices Change on the Real Estate Market?

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Rizun, Nina, Baj-Rogowska, Anna·2021·IEEE Access
DOI 10.1109/access.2021.3077860
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Abstract

This study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines the advantages of the complementary use of cross-correlation analysis and machine learning classification algorithms; (ii) applying the multi-class HPI values classifier which allows predicting the housing price increase, decrease or relative stability; (iii) exploiting the SVI that relates to interests in both `real estate' and `credit to buy real estate'; (iv) evaluation of the introduced approach in the context of the Polish real estate market. The main theoretical contribution of our work is a confirmation that the freely available information regarding Google user searches can provide an in-depth insight into enriching the generally accepted statistics on supply and demand in the real estate market. From the practical perspective, this research confirms that SVI can be associated as a sole determinant to anticipate the housing price change with time-lag sufficient for making decisions regarding the purchase (sale) of individual property or the real estate market control. Such findings can be also helpful for researchers who intend to use Google Tre…

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Metadata

Authors
Rizun, N., & Baj-Rogowska, A.
Affiliations
Gdańsk University of Technology (PL)
ORCID
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2021
Volume
9
Pages
70095-70117
ISSN
2169-3536 (ISSN-L)
DOI
10.1109/access.2021.3077860
OpenAlex
W3159731117
Cited by
26
References
1
Citations by year
2026: 5 · 2025: 6 · 2024: 8 · 2023: 3 · 2022: 4
FWCI
2.86
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Access (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Housing Market and Economics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
Keywords
Google Trends, search volume index, real estate market, web search queries, cross correlation function, real estate credit, Polish real estate market

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CoChat. (2026). Citation check: Can Web Search Queries Predict Prices Change on the Real Estate Market? https://app.cochat.ai/papers/10.1109/access.2021.3077860
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Rizun, N., & Baj-Rogowska, A. (2021). Can Web Search Queries Predict Prices Change on the Real Estate Market? IEEE Access. https://doi.org/10.1109/access.2021.3077860