The 8 requirements of real-time stream processing
ACM SIGMOD Record
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
Subword and spatiotemporal models for identifying actionable information in Haitian Kreyol
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Tweet me home: exploring information use on twitter in crisis situations
OCSC'11 Proceedings of the 4th international conference on Online communities and social computing
Crisees: real-time monitoring of social media streams to support crisis management
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
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News and disaster-related applications may benefit from real-time processing of large-volume, up-to-the-minute social media data. Our geo-mining algorithm finds local place references (of street, building, toponym and place abbreviation) in Twitter messages so that those messages can be put on a map. The ability to map is significant because it can present a timely overview of a situation. Our current research demonstrates that our prototype desktop algorithm that geo-locates Twitter messages with an F statistic of .90 accuracy for location identification will be viable on a large scale and in real time, for actual applications. We present methods of managing external resources, threading the algorithm and balancing the data load, that allow us to scale up the application without significantly re-writing the code.