Abstract:Location-Based Social Networks can be profitably exploited to characterize citizens' activities in urban environments. However, collecting LBSN is potentially challenging due to privacy concerns, connectivity issues, and potential imbalances in LBSN service usage. We propose to complement LBSN data with mobility data in the analysis of citizens' activities in urban areas. Unlike the explicit insights provided by LBSN users, mobility data give implicit feedback on citizens' habits. This paper explores the spati… Show more
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