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Early detection of emergency events from social media: a new text clustering approach

Author

Listed:
  • Lida Huang

    (Tsinghua University)

  • Panpan Shi

    (Gsafety Company)

  • Haichao Zhu

    (Gsafety Company)

  • Tao Chen

    (Tsinghua University)

Abstract

Emergency events require early detection, quick response, and accurate recovery. In the era of big data, social media users can be seen as social sensors to monitor real-time emergency events. This paper proposed an integrated approach to detect all four kinds of emergency events early, including natural disasters, man-made accidents, public health events, and social security events. First, the BERT-Att-BiLSTM model is used to detect emergency-related posts from massive and irrelevant data. Then, the 3 W attribute information (what, where, and when) of the emergency event is extracted. With the 3 W attribute information, we create an unsupervised dynamical event clustering algorithm based on text similarity and combine it with the supervised logistical regression model to cluster posts into different events. Experiments on Sina Weibo data demonstrate the superiority of the proposed framework. Case studies on some real emergency events show that the proposed framework has good performance and high timeliness. Practical applications of the framework are also discussed, followed by future directions for improvement.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:nathaz:v:111:y:2022:i:1:d:10.1007_s11069-021-05081-1
    DOI: 10.1007/s11069-021-05081-1
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    References listed on IDEAS

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    1. Yu Xiao & Qunying Huang & Kai Wu, 2015. "Understanding social media data for disaster management," 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. 79(3), pages 1663-1679, December.
    2. Hua Bai & Guang Yu, 2016. "A Weibo-based approach to disaster informatics: incidents monitor in post-disaster situation via Weibo text negative sentiment analysis," 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(2), pages 1177-1196, September.
    3. Xiangyang Guan & Cynthia Chen, 2014. "Using social media data to understand and assess disasters," 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. 74(2), pages 837-850, November.
    4. Qing Deng & Yi Liu & Hui Zhang & Xiaolong Deng & Yefeng Ma, 2016. "A new crowdsourcing model to assess disaster using microblog data in typhoon Haiyan," 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. 84(2), pages 1241-1256, November.
    5. Cynthia Chew & Gunther Eysenbach, 2010. "Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-13, November.
    6. Martin Rosvall & Carl T Bergstrom, 2010. "Mapping Change in Large Networks," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-7, January.
    7. Faxi Yuan & Rui Liu, 2018. "Crowdsourcing for forensic disaster investigations: Hurricane Harvey case study," 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. 93(3), pages 1529-1546, September.
    8. Kathryn C. Finch & Kassandra R. Snook & Carmen H. Duke & King-Wa Fu & Zion Tsz Ho Tse & Atin Adhikari & Isaac Chun-Hai Fung, 2016. "Public health implications of social media use during natural disasters, environmental disasters, and other environmental concerns," 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 729-760, August.
    9. 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.
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    Cited by:

    1. Yang, Zaoli & Wu, Qingyang & Venkatachalam, K. & Li, Yuchen & Xu, Bing & Trojovský, Pavel, 2022. "Topic identification and sentiment trends in Weibo and WeChat content related to intellectual property in China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).

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