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The goal of this paper is to infer features of urban ecology (i.e., social and economic activities, and social interaction) from spatiotemporal cell phone activity data. We present a novel approach that consists of (i) time series decomposition of the aggregate cell phone activity per unit area using spectral methods, (ii) clustering of areal units with similar activity patterns, and (ii) external validation using a ground truth data set we collected from municipal and online sources. The keydoi:10.1145/2746285.2746292 dblp:conf/mobihoc/CiciGMB15 fatcat:pktoensb4ben7o7yunwjkzblba