Social media analytics for natural disaster management

Zheye Wang, Xinyue Ye

Research output: Contribution to journalReview articlepeer-review

64 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)49-72
Number of pages24
JournalInternational Journal of Geographical Information Science
Volume32
Issue number1
DOIs
StatePublished - Jan 2 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Geography, Planning and Development
  • Library and Information Sciences

Keywords

  • Social media
  • census data
  • dimensions
  • natural disasters
  • remote sensing

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