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Extracting information nuggets from disaster- Related messages in social media
Muhammad Imran
Shady Elbassuoni
Carlos Castillo
Fernando Díaz
Patrick Meier
T. Comes, F.F., S. Fortier, J. Geldermann and T. Müller
Microblogging sites such as Twitter can play a vital role in spreading information during "natural" or man-made disasters. But the volume and velocity of tweets posted during crises today tend to be extremely high, making it hard for disaster-affected communities and professional emergency responders to process the information in a timely manner. Furthermore, posts tend to vary highly in terms of their subjects and usefulness; from messages that are entirely off-topic or personal in nature, to messages containing critical information that augments situational awareness. Finding actionable information can accelerate disaster response and alleviate both property and human losses. In this paper, we describe automatic methods for extracting information from microblog posts. Specifically, we focus on extracting valuable "information nuggets", brief, self-contained information items relevant to disaster response. Our methods leverage machine learning methods for classifying posts and information extraction. Our results, validated over one large disaster-related dataset, reveal that a careful design can yield an effective system, paving the way for more sophisticated data analysis and visualization systems.
urn:ISBN:9783923704804
openurl:?ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Fidl.iscram.org%2F&genre=proceeding&title=Extracting%20information%20nuggets%20from%20disaster-%20Related%20messages%20in%20social%20media&stitle=ISCRAM%202013&issn=2411-3387&isbn=9783923704804&date=2013&spage=791&epage=801&aulast=Muhammad%20Imran&au=Shady%20Elbassuoni&au=Carlos%20Castillo&au=Fernando%20D%EDaz&au=Patrick%20Meier&pub=Karlsruher%20Institut%20fur%20Technologie&place=KIT%3B%20Baden-Baden&sid=refbase%3AISCRAM
url:http://idl.iscram.org/show.php?record=613
citekey:MuhammadImran_etal2013
citation:Muhammad Imran, Shady Elbassuoni, Carlos Castillo, Fernando Díaz, & Patrick Meier. (2013). Extracting information nuggets from disaster- Related messages in social media. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 791-801). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
2013
ConferencePaper
text
Artificial intelligence
Data visualization
Disasters
Information retrieval
Information systems
Learning systems
Social networking (online)
Emergency responders
Extracting information
Machine learning methods
Situational awareness
Social media
Supervised classification
Twitter
Visualization system
Emergency services
file:http://idl.iscram.org/files/imran/2013/613_Imran_etal2013.pdf
Karlsruher Institut fur Technologie
English
2411-3387
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management
2013
791
801
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