数据科学
元数据
社会化媒体
计算机科学
分类
形势意识
社交媒体分析
维数(图论)
模式(遗传算法)
应急管理
分析
多样性(控制论)
地理空间分析
数据分析
万维网
情报检索
数据挖掘
地理
工程类
地图学
人工智能
法学
纯数学
航空航天工程
数学
政治学
标识
DOI:10.1080/13658816.2017.1367003
摘要
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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