Extracting information nuggets from disaster- Related messages in social media

Muhammad Imran, Shady Elbassuoni, Carlos Castillo, Fernando Diaz, Patrick Meier

Research output: Chapter in Book/Report/Conference proceedingConference contribution

179 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationISCRAM 2013 Conference Proceedings - 10th International Conference on Information Systems for Crisis Response and Management
PublisherKarlsruher Institut fur Technologie (KIT)
Pages791-801
Number of pages11
ISBN (Print)9783923704804
Publication statusPublished - 1 Jan 2013
Externally publishedYes
Event10th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2013 - Baden-Baden, Germany
Duration: 12 May 201315 May 2013

Other

Other10th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2013
CountryGermany
CityBaden-Baden
Period12/5/1315/5/13

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Keywords

  • Information extraction
  • Social media
  • Supervised classification
  • Twitter

ASJC Scopus subject areas

  • Information Systems

Cite this

Imran, M., Elbassuoni, S., Castillo, C., Diaz, F., & Meier, P. (2013). Extracting information nuggets from disaster- Related messages in social media. In ISCRAM 2013 Conference Proceedings - 10th International Conference on Information Systems for Crisis Response and Management (pp. 791-801). Karlsruher Institut fur Technologie (KIT).