PROGRESS IN GEOGRAPHY ›› 2020, Vol. 39 ›› Issue (8): 1412-1422.doi: 10.18306/dlkxjz.2020.08.014

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A review on the application of social media data in natural disaster emergency management

WU Kejie1,2(), WU Jidong1,2,*(), YE Mengqi1,2   

  1. 1. Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education of China, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    2. Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management & Ministry of Education, Beijing 100875, China
  • Received:2019-11-04 Revised:2020-04-05 Online:2020-08-28 Published:2020-10-28
  • Contact: WU Jidong E-mail:wukejiennu@163.com;wujidong@bnu.edu.cn
  • Supported by:
    National Key Research and Development Program of China(2018YFC1508903);National Natural Science Foundation of China(41571492)

Abstract:

Social media is a data source that is emerging but underutilized for disaster emergency management. There are few existing studies on the role of social media data in disaster emergency management in China, and international studies are also relatively scattered, which make relevant applications limited. This article reviewed the research on disaster management with social media data. We summarized the potential, advantages, and problems of applying social media data in disaster emergency management. The results show that: 1) Social media data are full of disaster information. They can support disaster early warning, real-time monitoring, and loss and rescue needs assessment, assist rapid emergency response, and predict possible disaster risks that relies on situational awareness and timely information. 2) The advantage of social media data is that it can ensure the timeliness and continuity of disaster information aquisition, which can provide disaster intensity maps, loss prediction, and public opinion analysis for disaster emergency management. 3) Some problems limit the accuracy of social media data analysis results, including limited geographical location information, lack of professional corpus, and complexity of information noise processing, among others. In order to make full use of the advantages of social media data to overcome the shortcomings of traditional observation and investigation methods and respond to disasters more scientifically, breakthroughs in social media data processing and multi-source data fusion analysis technology are needed.

Key words: social media, natural disaster, emergency management, machine learning