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The remarkable success of online social media sites marks a shift in the way people connect and share information. Much of this information now contains some form of geographical content because of the proliferation of location-aware devices, thus fostering the emergence ofgeosocialmedia – a new type of user-generated geospatial information. Through geosocial media we are able, for the first time, to observe human activities in scales and resolutions that were so far unavailable. Furthermore, the wide spectrum of social media data and service types provides a multitude of perspectives on real-world activities and happenings, thus opening new frontiers in geosocial knowledge discovery. However, gleaning knowledge from geosocial media is a challenging task, as they tend to be unstructured and thematically diverse. To address these challenges, this article presents a system prototype for harvesting, processing, modeling, and integrating heterogeneous social media feeds towards the generation of geosocial knowledge. Our article addresses primarily two key components of this system prototype: a novel data model for heterogeneous social media feeds and a corresponding general system architecture. We present these key components and demonstrate their implementation in our system prototype, GeoSocial Gauge. [ABSTRACT FROM AUTHOR]