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Using Social Media for Emergency Response and Urban Sustainability: A Case Study of the 2012 Beijing Rainstorm

Author

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  • Yandong Wang

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China)

  • Teng Wang

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China)

  • Xinyue Ye

    (School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan 430073, China
    Department of Geography, Kent State University, Kent, OH 44240, USA)

  • Jianqi Zhu

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China)

  • Jay Lee

    (Department of Geography, Kent State University, Kent, OH 44240, USA
    College of Environment and Planning, Henan University, Kaifeng 475001, China)

Abstract

With the proliferation of social media, information generated and disseminated from these outlets has become an important part of our everyday lives. For example, this type of information has great potential for effectively distributing political messages, hazard alerts, or messages of other social functions. In this work, we report a case study of the 2012 Beijing Rainstorm to investigate how emergency information was timely distributed using social media during emergency events. We present a classification and location model for social media text streams during emergency events. This model classifies social media text streams based on their topical contents. Integrated with a trend analysis, we show how Sina-Weibo fluctuated during emergency events. Using a spatial statistical analysis method, we found that the distribution patterns of Sina-Weibo were related to the emergency events but varied among different topics. This study helps us to better understand emergency events so that decision-makers can act on emergencies in a timely manner. In addition, this paper presents the tools, methods, and models developed in this study that can be used to work with text streams from social media in the context of disaster management and urban sustainability.

Suggested Citation

  • Yandong Wang & Teng Wang & Xinyue Ye & Jianqi Zhu & Jay Lee, 2015. "Using Social Media for Emergency Response and Urban Sustainability: A Case Study of the 2012 Beijing Rainstorm," Sustainability, MDPI, vol. 8(1), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:8:y:2015:i:1:p:25-:d:61402
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    References listed on IDEAS

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    Cited by:

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    2. Yuqi Zang & Jiamei Zhao & Wenchao Jiang & Tong Zhao, 2024. "Advanced Linguistic Complex T-Spherical Fuzzy Dombi-Weighted Power-Partitioned Heronian Mean Operator and Its Application for Emergency Information Quality Assessment," Sustainability, MDPI, vol. 16(7), pages 1-36, April.
    3. Jiyong Ding & Juefang Cai & Guangxiang Guo & Chen Chen, 2018. "An Emergency Decision-Making Method for Urban Rainstorm Water-Logging: A China Study," Sustainability, MDPI, vol. 10(10), pages 1-21, September.
    4. Jedsada Phengsuwan & Tejal Shah & Nipun Balan Thekkummal & Zhenyu Wen & Rui Sun & Divya Pullarkatt & Hemalatha Thirugnanam & Maneesha Vinodini Ramesh & Graham Morgan & Philip James & Rajiv Ranjan, 2021. "Use of Social Media Data in Disaster Management: A Survey," Future Internet, MDPI, vol. 13(2), pages 1-24, February.
    5. Jia He & Miao Ma & Yuxuan Zhou & Miaoke Wang, 2023. "What We Have Learned about the Characteristics and Differences of Disaster Information Behavior in Social Media—A Case Study of the 7.20 Henan Heavy Rain Flood Disaster," Sustainability, MDPI, vol. 15(6), pages 1-18, March.
    6. Rizwan Muhammad & Yaolong Zhao & Fan Liu, 2019. "Spatiotemporal Analysis to Observe Gender Based Check-In Behavior by Using Social Media Big Data: A Case Study of Guangzhou, China," Sustainability, MDPI, vol. 11(10), pages 1-30, May.
    7. Zheye Wang & Xinyue Ye & Ming-Hsiang Tsou, 2016. "Spatial, temporal, and content analysis of Twitter for wildfire hazards," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 523-540, August.
    8. Mahsa Dalili Shoaei & Meisam Dastani, . "The Role of Twitter During the COVID-19 Crisis: A Systematic Literature Review," Acta Informatica Pragensia, Prague University of Economics and Business, vol. 0.
    9. Mingyun Gu & Haixiang Guo & Jun Zhuang & Yufei Du & Lijin Qian, 2022. "Social Media User Behavior and Emotions during Crisis Events," IJERPH, MDPI, vol. 19(9), pages 1-21, April.
    10. Mahsa Dalili Shoaei & Meisam Dastani, 2020. "The Role of Twitter During the COVID-19 Crisis: A Systematic Literature Review," Acta Informatica Pragensia, Prague University of Economics and Business, vol. 2020(2), pages 154-169.
    11. Lida Huang & Panpan Shi & Haichao Zhu & Tao Chen, 2022. "Early detection of emergency events from social media: a new text clustering approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(1), pages 851-875, March.

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