The predictive power of online chatter
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Beyond Microblogging: Conversation and Collaboration via Twitter
HICSS '09 Proceedings of the 42nd Hawaii International Conference on System Sciences
Why We Twitter: An Analysis of a Microblogging Community
Advances in Web Mining and Web Usage Analysis
How and why people Twitter: the role that micro-blogging plays in informal communication at work
Proceedings of the ACM 2009 international conference on Supporting group work
Backchannel persistence and collaborative meaning-making
Proceedings of the 27th ACM international conference on Design of communication
Proceedings of the 37th annual ACM SIGUCCS fall conference: communication and collaboration
Proceedings of the 2009 International Workshop on Location Based Social Networks
Using twitter to recommend real-time topical news
Proceedings of the third ACM conference on Recommender systems
The Twitter Book
Proceedings of the 2nd ACM workshop on Social web search and mining
Chatter on the red: what hazards threat reveals about the social life of microblogged information
Proceedings of the 2010 ACM conference on Computer supported cooperative work
Genetic Location-Based Social Networks (G-LBSN)
Proceedings of the 3rd International Workshop on Location and the Web
"Voluntweeters": self-organizing by digital volunteers in times of crisis
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using stranger as sensors: temporal and geo-sensitive question answering via social media
Proceedings of the 22nd international conference on World Wide Web
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People in the locality of earthquakes are publishing anecdotal information about the shaking within seconds of their occurrences via social network technologies, such as Twitter. In contrast, depending on the size and location of the earthquake, scientific alerts can take between two to twenty minutes to publish. We describe TED (Twitter Earthquake Detector) a system that adopts social network technologies to augment earthquake response products and the delivery of hazard information. The TED system analyzes data from these social networks for multiple purposes: 1) to integrate citizen reports of earthquakes with corresponding scientific reports 2) to infer the public level of interest in an earthquake for tailoring outputs disseminated via social network technologies and 3) to explore the possibility of rapid detection of a probable earthquake, within seconds of its occurrence, helping to fill the gap between the earthquake origin time and the presence of quantitative scientific data.