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Social Media Behaviour Analysis in Disaster-Response Messages of Floods and Heat Waves via Artificial Intelligence

Author

Listed:
  • Víctor Ponce-López
  • Catalina Spataru

Abstract

This paper analyses social media data in multiple disaster-related collections of floods and heat waves in the UK. The proposed method uses machine learning classifiers based on deep bidirectional neural networks trained on benchmark datasets of disaster responses and extreme events. The resulting models are applied to perform a qualitative analysis via topic inference in text data. We further analyse a set of behavioural indicators and match them with climate variables via decoding synoptical records to analyse thermal comfort. We highlight the advantages of aligning behavioural indicators along with climate variables to provide with 7 additional valuable information to be considered especially in different phases of a disaster and applicable to extreme weather periods. The positiveness of messages is around 8% for disaster, 1% for disaster and medical response, 7% for disaster and humanitarian related messages. This shows the reliability of such data for our case studies. We show the transferability of this approach to be applied to any social media data collection.

Suggested Citation

  • Víctor Ponce-López & Catalina Spataru, 2022. "Social Media Behaviour Analysis in Disaster-Response Messages of Floods and Heat Waves via Artificial Intelligence," Computer and Information Science, Canadian Center of Science and Education, vol. 15(3), pages 1-18, August.
    • Handle: RePEc:ibn:cisjnl:v:15:y:2022:i:3:p:18
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    References listed on IDEAS

    as
    1. Yagci Sokat, Kezban & Zhou, Rui & Dolinskaya, Irina S. & Smilowitz, Karen & Chan, Jennifer, 2016. "Capturing Real-Time Data in Disaster Response Logistics," Journal of Operations and Supply Chain Management (JOSCM), Fundação Getulio Vargas, Escola de Administração de Empresas de São Paulo (FGV EAESP), vol. 9(1), July.
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    Cited by:

    1. Yoshiki B. Kurata & Ardvin Kester S. Ong & Ranice Ysabelle B. Ang & John Karol F. Angeles & Bianca Danielle C. Bornilla & Justine Lian P. Fabia, 2023. "Factors Affecting Flood Disaster Preparedness and Mitigation in Flood-Prone Areas in the Philippines: An Integration of Protection Motivation Theory and Theory of Planned Behavior," Sustainability, MDPI, vol. 15(8), pages 1-24, April.

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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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