Comber, A. orcid.org/0000-0002-3652-7846, Asher, M., Wang, Y. et al. (5 more authors) (2025) Characterising neighbourhood dynamics through social media anlaysis and house sales transactions. AGILE GIScience Series, 6. 18. ISSN 2700-8150
Abstract
This paper describes a two stage approach for identifying neighbourhood areas that may be undergoing gentrification related changes. It summarises classic hedonic house price data over time (2014–2023) for each neighbourhood, and compares neighbourhood average price with those of local nearby areas. This enables neighbourhoods experiencing high relative increases in price to be identified as potentially gentrifying areas. Social media data for these areas were extracted and analysed using a large language model which scored each individual social media post by the degree to which their content indicated that the neighbourhood is experiencing change, potentially providing confirmatory evidence or not of gentrification. A number of areas of further work are identified.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License |
Keywords: | neighbourhood dynamics, house price model, Twitter |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) |
Funding Information: | Funder Grant number ESRC (Economic and Social Research Council) ES/Y006259/1 ESRC (Economic and Social Research Council) ES/L011891/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Jul 2025 14:18 |
Last Modified: | 11 Jul 2025 14:18 |
Published Version: | https://agile-giss.copernicus.org/articles/6/18/20... |
Status: | Published |
Publisher: | Copernicus Publications |
Identification Number: | 10.5194/agile-giss-6-18-2025 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:229047 |