MovementFinder: Visual analytics of origin-destination patterns from geo-tagged social media

Geo-tagged social media data can be viewed as sampling of people´s trajectories in daily life. It consists of people´s movements and embeds the semantics of movements. However, it is challenging to reveal patterns from the sparse and irregular sampling data. We proposed an interactive multi-filter visualization approach to analyze the spatial-temporal movement pattern in people´s daily life. People´s trajectories are visualized on the map with multiple functional layers. With our visual analytics tools, users are able to drill down to details, with the awareness of the origin-destination flow patterns of spatial, temporal, and semantic meaning.