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Research Article | Open Access

Exploring the evolutionary characteristics of social media data in metro emergencies: A case study of Zhengzhou Metro flood

Yiqi Zhou1Fucai Hua2Junfeng Chen1Maohua Zhong1,3( )
Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing 100084, China
Beijing Urban Construction Design & Development Group Co., Limited, Beijing 100037, China
Tsinghua University (Department of Engineering Physics)–Beijing Urban Construction Design & Development Group Co., Limited Joint Research Center for Urban Disaster Prevention and Safety, Beijing 100084, China
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With the development of urban transportation, metros have become an important means of travel for residents. However, casualty and economic loss might occur in metro systems due to various emergencies. Social media has gradually become the main way to express people’s needs, which provides a new analysis perspective for risk management in metros. This study takes the Zhengzhou Metro flood as an example and collects relevant social media data. Then, the analysis method of social media data evolution characteristics in metro emergencies is proposed. Finally, the evolution characteristics of social media data are analyzed from three aspects: spatiotemporal distribution, emotional distribution, and hot topics classification. The results show that: The temporal distribution of social media data is affected by the emergency process and official media; the spatial distribution of social media data reflects the distribution of stations affected by emergency and temporary shelters; timely and appropriate official media reports are conducive to guiding public emotions toward positive; and the key hot topics can be divided into disaster environment (DE), disaster impact (DI), disaster carrier (DC), emergency management (EM), positive comment (PC), and negative comment (NC). The proposed method can provide support for public opinion analysis and risk management in metro emergencies.


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Journal of Intelligent Construction
Pages 9180027-9180027
Cite this article:
Zhou Y, Hua F, Chen J, et al. Exploring the evolutionary characteristics of social media data in metro emergencies: A case study of Zhengzhou Metro flood. Journal of Intelligent Construction, 2023, 1(4): 9180027.
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Received: 18 September 2023
Revised: 26 October 2023
Accepted: 27 October 2023
Published: 18 December 2023
© The Author(s) 2023. Published by Tsinghua University Press.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.