Abstract

Being able to assess the impact of government-led investment onto socio-economic indicators in cities has long been an important target of urban planning. However, owing to the lack of large-scale data with a fine spatio-temporal resolution, there have been limitations in terms of how planners can track the impact and measure the effectiveness of cultural investment in small urban areas. Taking advantage of nearly 4 million transition records for 3 years in London from a popular location-based social network service, Foursquare, we study how the socio-economic impact of government cultural expenditure can be detected and predicted. Our analysis shows that network indicators such as average clustering coefficient or centrality can be exploited to estimate the likelihood of local growth in response to cultural investment. We subsequently integrate these features in supervised learning models to infer socio-economic deprivation changes for London’s neighbourhoods. This research presents how geosocial and mobile services can be used as a proxy to track and predict socio-economic deprivation changes as government financial effort is put in developing urban areas and thus gives evidence and suggestions for further policymaking and investment optimization.

Highlights

  • In 1997, the striking ‘Bilbao miracle’ created by Guggenheim Museum provided Bilbao, a depressed northern Spanish port town, with a dramatic socio-economic growth, and demonstrated that cities can blossom with cultural investment [1,2]

  • We have investigated the socio-economic impact of cultural expenditure on London neighbourhoods, visible through the lens of location-based mobile data

  • We have explored the relationship between socio-economic condition, cultural investment and geosocial network graph, finding that spending more on culture can lead to an improvement of local development, especially for more deprived neighbourhoods

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Summary

Introduction

In 1997, the striking ‘Bilbao miracle’ created by Guggenheim Museum provided Bilbao, a depressed northern Spanish port town, with a dramatic socio-economic growth, and demonstrated that cities can blossom with cultural investment [1,2]. Local regeneration has received general acceptance, large-scale evaluation and prediction of its impact 2 are still not widely practiced. The potential of network science in offering insight on deprivation dynamics [3] along with the millions of human mobility traces made available by location-based applications has so far been largely untapped in culture-led regeneration studies. We propose a new fusion of techniques using geosocial network data from Foursquare to quantify the effect of cultural investment on the urban regeneration process and predict its outcome in London’s neighbourhoods

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