Application of Social Sensors in Natural Disasters Emergency Management: A Review

Kaize Shi, Xueping Peng, Hao Lu, Yifan Zhu, Zhendong Niu*

*Corresponding author for this work

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Abstract

Natural disasters are public emergencies characterized by suddenness, universality, and nonconventionality. Realizing the early warning, monitoring, and intervention of natural disasters and their derivative social impacts is significant for reducing the disasters' damage and benefits the maintenance of social stability. Social sensors are ubiquitous sensors based on social network platforms. It uses the concepts and methods of physical space to mine social signals that integrate human perception and intelligence in cyberspace. Compared with traditional physical sensors, social sensors represent a crucial data acquisition channel in the emergency management of natural disasters and have the advantages of real time, comprehensive coverage, low cost, and flexible deployment. This article reviews the application of social sensors in natural disasters emergency management. We summarize the application functions of social sensors into three categories: natural disaster situation awareness and event detection, disaster information dissemination and communication, and disaster sentiment analysis and public opinion mining. Based on the above functions, this article analyzes the research status, data, technical methods, and application systems. Finally, this article proposes a research trend of applying social sensors in natural disaster emergency management according to the requirements of real scenarios.

Original languageEnglish
Pages (from-to)3143-3158
Number of pages16
JournalIEEE Transactions on Computational Social Systems
Volume10
Issue number6
DOIs
Publication statusPublished - 1 Dec 2023

Keywords

  • Decision support system
  • emergency management
  • parallel system
  • social network analysis
  • social sensor
  • sudden natural disaster

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Shi, K., Peng, X., Lu, H., Zhu, Y., & Niu, Z. (2023). Application of Social Sensors in Natural Disasters Emergency Management: A Review. IEEE Transactions on Computational Social Systems, 10(6), 3143-3158. https://doi.org/10.1109/TCSS.2022.3211552