Social media analytics for natural disaster management. Issue 1 (2nd January 2018)

• Record Type: Journal Article
• Authors: Wang, Zheye; Ye, Xinyue
• Is Part Of: International journal of geographical information science. Volume 32:Issue 1(2018)
• Page Start: 49
• Page End: 72
• Publication Date: 2018-01-02
• Subjects: Social media -- dimensions -- natural disasters -- census data -- remote sensing; Geography -- Data processing -- Periodicals; Information storage and retrieval systems -- Periodicals; Géomatique -- Périodiques; Systèmes d'information -- Périodiques; 910.285
• DOI: 10.1080/13658816.2017.1367003
• Languages: English
• ISSNs: 1365-8816

Abstract

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.