Data from: Quantifying the link between art and property prices in urban neighbourhoods

Seresinhe, Chanuki I.

Preis, Tobias, University of Warwick

Moat, Helen Susannah, University of Warwick

Published Mar 29, 2016 on Dryad. https://doi.org/10.5061/dryad.6q5vf

Cite this dataset

Seresinhe, Chanuki I.; Preis, Tobias; Moat, Helen Susannah (2016). Data from: Quantifying the link between art and property prices in urban neighbourhoods [Dataset]. Dryad. https://doi.org/10.5061/dryad.6q5vf

Abstract

Is there an association between art and changes in the economic conditions of urban neighbourhoods? While the popular media and policymakers commonly believe this to be the case, quantitative evidence remains lacking. Here, we use metadata of geotagged photographs uploaded to the popular image-sharing platform Flickr to quantify the presence of art in London neighbourhoods. We estimate the presence of art in neighbourhoods by determining the proportion of Flickr photographs which have the word ‘art’ attached. We compare this with the relative gain in residential property prices for each Inner London neighbourhood. We find that neighbourhoods which have a higher proportion of ‘art’ photographs also have greater relative gains in property prices. Our findings demonstrate how online data can be used to quantify aspects of the visual environment at scale and reveal new connections between the visual environment and crucial socio-economic measurements.

Usage notes

Data for Quantifying the Link Between Art and Property Prices in Urban Neighbourhoods

The variable "Rank.Mean.Change" is calculated using data from residential property sales registered at the Land Registry from 2004 to 2013 (https://www.gov.uk/government/collections/price-paid-data). We calculate the mean residential property price per London postcode district. We rank the postcodes according to mean residential property price, where a rank of 1 indicates the highest mean residential property price. We calculate the variable "Rank.Mean.Change", the relative changes in property price, by determining the difference between the 2013 rank and the 2004 rank for each London postcode district. "Proportion.Art.Photos" is calculated using data from the popular image sharing website Flickr. For photographs in each London postcode district, we deem a photo as "art" related if there is a mention of "art" in its associated textual metadata. We search all the textual elements of each image, including the title, description and tags, using the following regular expression " \ ". We divide the number of "art" images by the total number of images for each postcode for the whole time period (2004 to 2013), in order to create a normalised indicator of "art" per area: "Proportion.Art.Photos".

London_Prices_Flickr_Art_Agg.csv

Location

London