Towards Web-Scale Geo-Semantic Crowd Discovery

2010 Specialist Meeting—Spatio-Temporal Constraints on Social Networks, UCSB

James Caverlee

“There is a growing need to fundamentally advance research for enabling a new generation of applications for monitoring, analyzing, and distilling information from the prospective web of real-time content that reflects the current activity of the web’s participants. Highlydynamic real-time social systems like Twitter, Facebook, and Google Buzz have already published terabytes of real-time human “sensor” data in the form of status updates. Coupled with growing location-based social media services like Gowalla, Foursquare, and Google Latitude, we can see unprecedented access to the activities, actions, and trails of millions of people, with the promise of deeper and more insightful understanding of the emergent collective knowledge (“wisdom of the crowds”) embedded in these activities and actions. Toward the goal of web-scale social media mining and inference, our lab (http://infolab.tamu.edu) is pursuing a set of related research activities, two of which are briefly described here: (i) Identifying and tracking the evolution of semantic crowds; and (i) Social media location estimation.”

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