A twitter tale of three hurricanes: Harvey, Irma, and Maria

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

31 Citations (Scopus)

Abstract

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 di erent 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.

Original languageEnglish
Title of host publicationConference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2018
EditorsBrian Tomaszewski, Kees Boersma
PublisherInformation Systems for Crisis Response and Management, ISCRAM
Pages553-572
Number of pages20
ISBN (Electronic)9780692127605
Publication statusPublished - 2018
Event15th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2018 - Rochester, United States
Duration: 20 May 201823 May 2018

Publication series

NameProceedings of the International ISCRAM Conference
Volume2018-May
ISSN (Electronic)2411-3387

Conference

Conference15th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2018
Country/TerritoryUnited States
CityRochester
Period20/05/1823/05/18

Keywords

  • Disaster management
  • Image processing
  • Named-entity recognition
  • Social media
  • Text classification
  • Topic modeling

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