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We propose Textiverse, a big data approach for mining geotagged timestampedtextual data on a map, such as for Twitter feeds, crime reports, or restaurantreviews. We use a scalable data management pipeline that extracts keyphrasesfrom online databases in parallel. We speed up this time-consuming step so thatit outpaces the content creation rate of popular social media. The result ispresented in a web-based interface that integrates with Google Maps tovisualize textual content of massive scale. The visual design is based onaggregating spatial regions into discrete sites and rendering each such site asa circular tag cloud. To demonstrate the intended use of our technique, wefirst show how it can be used to characterize the U.S.\ National ScienceFoundation funding status based on all 489,151 awards. We then apply the sametechnique on visually representing a more spatially scattered andlinguistically informal dataset: 1.2 million Twitter posts about the Androidmobile operating system.

Textiverse: A Scalable Visual Analytics System for Exploring Geotagged and Timestamped Text Corpora