Social Information Improves Location Prediction in the Wild

Abstract

How can knowing the location of my friends be used to more accurately predict my location? This paper explores socially-aware location prediction under a particularly challenging setting where the underlying interactions and social network are unknown and must be inferred over continuous spatiotemporal data. Our method samples inferred network topology using a linear regression model to predict future individual locations. We present an in-depth empirical study comparing different network models and network sampling regimes under a bootstrapped sampling baseline. Furthermore, our qualitative analysis demonstrates the value of social information in population mobility modeling under our application’s challenges.