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Real-time web / Social media / Text messaging / Websites / Microblogging / Twitter usage / Twitter / World Wide Web / Technology


Identifying Valuable Information from Twitter During Natural Disasters Brandon Truong, Cornelia Caragea Computer Science and Engineering University of North Texas [removed], [removed]
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Document Date: 2014-11-13 13:58:33

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File Size: 198,78 KB

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City

Seattle / /

Company

Cambridge University Press / IEEE Intelligent Systems / Twitter Social Networks / Mei / /

Country

Japan / United States / United Kingdom / Chile / /

/

Event

Natural Disaster / /

Facility

Engineering University of North / /

IndustryTerm

news media / Internet slang Internet abbreviations / disaster-related systems / machine learning algorithms / social media data mining research / Web Vol. / data mining / social media communications / actual web page / data mining toolkit1 / informative social media filtering / public social media / Social media / electricity / social media data / natural language processing / social network / /

Organization

Cambridge University / Information Society / National Science Foundation / University of North Texas / Pennsylvania State University / Caragea Computer Science and Engineering University / OpenSource Geospatial Intelligence / US Geospatial Intelligence Foundation / Herndon / /

Person

Sam Stehle / Cornelia Caragea / Terrence Liu / Daniel Stieben / Kishore Neppalli / Van De Walle / Andrea H. Tapia / Anna Squicciarini / /

Position

RT / author / Conversational RT / representative / /

Product

OpenNLP Java Libraries / /

ProgrammingLanguage

Java / /

ProvinceOrState

Virginia / New York / /

PublishedMedium

IEEE Intelligent Systems / The Information Society / The Swedish Journal / /

Region

North Texas / /

Technology

machine learning algorithms / machine learning / natural language processing / Java / data mining / /

URL

http /

SocialTag