Foundations of a Multilayer Annotation Framework for Twitter Communications During Crisis Events

William J. Corvey, Sudha Verma, Sarah Vieweg, Martha Palmer, James H. Martin

Abstract
In times of mass emergency, vast amounts of data are generated via computer-mediated communication (CMC) that are difficult to manually collect and organize into a coherent picture. Yet valuable information is broadcast, and can provide useful insight into time- and safety-critical situations if captured and analyzed efficiently and effectively. We describe a natural language processing component of the EPIC (Empowering the Public with Information in Crisis) Project infrastructure, designed to extract linguistic and behavioral information from tweet text to aid in the task of information integration. The system incorporates linguistic annotation, in the form of Named Entity Tagging, as well as behavioral annotations to capture tweets contributing to situational awareness and analyze the information type of the tweet content. We show classification results and describe future integration of these classifiers in the larger EPIC infrastructure.
Anthology ID:
L12-1598
Volume:
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
Month:
May
Year:
2012
Address:
Istanbul, Turkey
Venue:
LREC
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Publisher:
European Language Resources Association (ELRA)
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URL:
http://www.lrec-conf.org/proceedings/lrec2012/pdf/1008_Paper.pdf
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Cite (ACL):
William J. Corvey, Sudha Verma, Sarah Vieweg, Martha Palmer, and James H. Martin. 2012. Foundations of a Multilayer Annotation Framework for Twitter Communications During Crisis Events. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), Istanbul, Turkey. European Language Resources Association (ELRA).
Cite (Informal):
Foundations of a Multilayer Annotation Framework for Twitter Communications During Crisis Events (Corvey et al., LREC 2012)
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http://www.lrec-conf.org/proceedings/lrec2012/pdf/1008_Paper.pdf
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