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Social media analytics for natural disaster management

Wang, Zheye, Ye, Xinyue·2018·International Journal of Geographical Information Science

Abstract

Social media analytics has become prominent in natural disaster management. In spite of a large variety of metadata fields in social media data, four dimensions (i.e. space, time, content and network) have been given particular attention for mining useful information to gain situational awareness and improve disaster response. In this article, we review how existing studies analyze these four dimensions, summarize common techniques for mining these dimensions, and then suggest some methods accordingly. We then propose a schema to categorize the gathered articles into 15 classes and facilitate the generation of data analysis tasks. We find that (1) a large part of studies involve multiple dimensions of social media data in their analyses, (2) there are both separate analyses for each dimension and simultaneous analyses for multiple dimensions and (3) there are fewer simultaneous analyses as dimensions increase. Finally, we suggest research opportunities and challenges in fusing social media data with authoritative datasets, i.e. census data and remote-sensing data.

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Metadata

Authors
Wang, Z., & Ye, X.
Venue
International Journal of Geographical Information Science
Published
2017-08-22
Volume
32
Issue
1
Pages
49-72
ISSN
  • 0269-3798 (ISSN-L)
  • 1365-8816
  • 1362-3087
OpenAlex
W2750351539
Cited by
314
References
5
FWCI
52.41
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Social media analytics for natural disaster management. https://app.cochat.ai/papers/10.1080/13658816.2017.1367003
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Wang, Z., & Ye, X. (2018). Social media analytics for natural disaster management. International Journal of Geographical Information Science. https://doi.org/10.1080/13658816.2017.1367003

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