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A review of deep learning techniques for disaster management in social media: trends and challenges

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Abstract

In the present era, social media platforms have increasingly become invaluable sources of information and connectivity. Twitter(X) is one of the social media landscape’s most prominent and influential components. Certainly, Twitter data offers substantial value across a range of disaster-related applications. Its utility extends to real-time event detection, classifying diverse crisis types, and analyzing evolving sentiments throughout such events. A disaster is a catastrophic event that leads to significant disruption in the everyday operations of a community. This paper reviews the trends and challenges associated with using social media in disaster management. As part of this paper, we systematically and consistently examine several crises-including natural hazards, human-induced disasters, and health-related disasters. Different information types and sources are prevalent in different crises, leading to insights into their prevalence.

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  1. Department of Computer Science and Engineering, VIT-AP University, Amaravati, Andhra Pradesh, India

    T. D. N. Pavani & SreeJagadeesh Malla

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Pavani, T.D.N., Malla, S. A review of deep learning techniques for disaster management in social media: trends and challenges. Eur. Phys. J. Spec. Top. (2024). https://doi.org/10.1140/epjs/s11734-024-01172-9

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