This article focuses on the use of big data for urban geography research. We collect data from the location-based service Foursquare in The Netherlands and employ it to obtain a rich catalogue of restaurant locations and other urban amenities, as well as a measure of their popularity among users. Because the Foursquare data can be combined with traditional sources of socio-economic data obtained from Statistics Netherlands, we can quantify, document and characterise some of the biases inherent in these new sources of data in the context of urban applications. A detailed analysis is given as to when this type of big data is useful and when it is misleading. Although the users of Foursquare are not representative of the whole population, we argue that this inherent bias can be exploited for research about the attractiveness of urban landscapes and consumer amenities in addition to the more traditional data on urban amenities.
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- foursquare, diversity/cohesion/segregation, method, neighbourhood, urban amenities, diversity, CONSUMER, cohesion, segregation, Foursquare