Studying human movement citywide is important for understanding the mobility and transportation patterns. Rather than investigating the trajectories of individuals, we employ an Eulerian approach to analyze the crowd flows among a geographical network and a social network, which are extracted from the mobile phone data. We design a suite of visualization techniques to illustrate the dynamic evolutions of the flow over the networks. We contribute the design and implementation of a visual

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... s system, called MobilityViewer, that supports situation-aware understanding and visual reasoning of human mobility. We exemplify our approach with a real citywide dataset of 7 millions users in two months.