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- W1119287486 abstract "People around the world use social media platforms such as Twitter to express their opinion and share activities about various aspects of daily life. In the same way social media changes communication in daily life, it also is transforming the way individuals communicate during disasters and emergencies. Because emergency officials have come to rely on social media to communicate alerts and updates, they must learn how users communicate disaster related content on social media. We used a novel information-theoretic unsupervised learning tool, CorEx, to extract and characterize highly relevant content used by the public on Twitter during known emergencies, such as fires, explosions, and hurricanes. Using the resulting analysis, authorities may be able to score social media content and prioritize their attention toward those messages most likely to be related to the disaster." @default.
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- W1119287486 date "2015-05-18" @default.
- W1119287486 modified "2023-09-27" @default.
- W1119287486 title "Disentangling the Lexicons of Disaster Response in Twitter" @default.
- W1119287486 cites W2142074516 @default.
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- W1119287486 doi "https://doi.org/10.1145/2740908.2741728" @default.
- W1119287486 hasPublicationYear "2015" @default.
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