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A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria
Firoj Alam
author
Ferda Ofli
author
Muhammad Imran
author
Michael Aupetit
author
2018
Rochester Institute of Technology
Rochester, NY (USA)
English
People increasingly use microblogging platforms such as Twitter during natural disasters and emergencies. Research studies have revealed the usefulness of the data available on Twitter for several disaster response tasks. However, making sense of social media data is a challenging task due to several reasons such as limitations of available tools to analyze high-volume and high-velocity data streams. This work presents an extensive multidimensional analysis of textual and multimedia content from millions of tweets shared on Twitter during the three disaster events. Specifically, we employ various Artificial Intelligence techniques from Natural Language Processing and Computer Vision fields, which exploit different machine learning algorithms to process the data generated during the disaster events. Our study reveals the distributions of various types of useful information that can inform crisis managers and responders as well as facilitate the development of future automated systems for disaster management.
social media
artificial intelligence
image processing
supervised classification
disaster management
exported from refbase (http://idl.iscram.org/show.php?record=2131), last updated on Mon, 25 Nov 2019 10:45:39 +0100
text
http://idl.iscram.org/files/firojalam/2018/2131_FirojAlam_etal2018.pdf
FirojAlam_etal2018
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management
Iscram 2018
Kees Boersma
editor
Brian Tomaszeski
editor
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management
2018
Rochester Institute of Technology
Rochester, NY (USA)
conference publication
553
572
978-0-692-12760-5
2411-3387
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