Real-Time Crisis Mapping Using Language Distribution

Justin Sampson, Fred Morstatter, Reza Zafarani, Huan Liu

Research output: Chapter in Book/Entry/PoemConference contribution

3 Scopus citations

Abstract

With the increase in GPS-enabled devices, socialmedia sites, such as Twitter, are quickly becoming a primeoutlet for timely geo-spatial data. Such data can be leveragedto aid in emergency response planning and recovery operations. Unfortunately, the information overload poses significantdifficulty to the quick discovery and identification ofemergency situation areas. The system tackles this challengeby providing real-time mapping of influence areas based onautomatic analysis of the flow of discussion using languagedistributions. The workflow is then further enhanced throughthe addition of keyword surprise mapping which projects the general divergence map onto specific task-level keywords for precise and focused response.

Original languageEnglish (US)
Title of host publicationProceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
EditorsXindong Wu, Alexander Tuzhilin, Hui Xiong, Jennifer G. Dy, Charu Aggarwal, Zhi-Hua Zhou, Peng Cui
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1648-1651
Number of pages4
ISBN (Electronic)9781467384926
DOIs
StatePublished - Jan 29 2016
Event15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 - Atlantic City, United States
Duration: Nov 14 2015Nov 17 2015

Publication series

NameProceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

Other

Other15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
Country/TerritoryUnited States
CityAtlantic City
Period11/14/1511/17/15

Keywords

  • Crisis Mapping
  • Data Visualization
  • Information Overload
  • Social Media

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications

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