document: Find me if you can : improving geographical prediction with social and spatial proximity Geography and social relationships are inextricably intertwined ; the people we interact with on a daily basis almost always live near us . As people spend more time online , data regarding these two dimensions -- geography and social relationships -- are becoming increasingly precise , allowing us to build reliable models to describe their interaction . These models have important implications in the design of location-based services , security intrusion detection , and social media supporting local communities . Using user-supplied address data and the network of associations between members of the Facebook social network , we can directly observe and measure the relationship between geography and friendship . Using these measurements , we introduce an algorithm that predicts the location of an individual from a sparse set of located users with performance that exceeds IP-based geolocation . This algorithm is efficient and scalable , and could be run on a network containing hundreds of millions of users .
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