Geo-spotting: mining online location-based services for optimal retail store placement
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
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Measuring the spatial distribution of locations of many entities (trees, atoms, economic activities, ...), and, more precisely, the deviations from purely random configurations, is a powerful method to unravel their underlying interactions. I study here the spatial organization of retail commercial activities. From pure location data, network analysis leads to a community structure that closely follows the commercial classification of the US Department of Labor. The interaction network allows to build a 'quality' index of optimal location niches for stores, which has been empirically tested.