Mining Urban Deprivation from Foursquare: Implicit Crowdsourcing of City Land Use

摘要

Research has shown a relationship between the physical characteristics of a city neighborhood (such as the presence of playgrounds and fast-food outlets) and neighborhood deprivation as defined in socioeconomic indices. Official land-use data has often been the source for such research. This article examines the viability of using social-networking data as an alternative source. The authors study all venues on the Foursquare location-mapping application across a variety of London census areas. They study the relationship between the presence of different venues in an area and its score on the socioeconomic Index of Multiple Deprivation. They conclude that knowing which venues are hosted by which community offers not only insights into neighborhood deprivation but also a reasonable way of predicting community deprivation scores at fine-grained temporal resolutions. This article is part of a special issue on pervasive analytics and citizen science.