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With the digital turn, data from connected devices are a new resource for understanding urban rhythms and mobility. Using the geolocated messages (1, 540, 000 tweets) of Twitter social network users recorded in 2015, this article uses dynamic graphs to visualize Parisian mobilities. Using a clustering algorithm, we show how to move from a geolocated message to an individual displacement and on to collective trajectories. These trajectories illustrate the preferential mobility of users of the social network in Paris, as well as the areas of concentration and poles of interest.