We present a visual analytics system that supports the geospatiotemporal analysis of social media data based on a large-scale distributed topic modeling technique. Through the analysis of social media data in a given time and region, we can identify critical events in real time. However, it takes significant time to perform such analyses against a large amount of social media data. As a way to handle this issue, we developed an efficient tile-based topic modeling approach, which divides textual data into multiple subsets with respect to different regions and time frames at different zoom levels and applies topic modeling to each subset.

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