Abstract
Recent advances in social media have unveiled their potential of providing real-time solutions for disaster management. The work proposed in this paper utilizes Twitter posts to improve flow of information during crisis situations in order to provide support and save lives. The proposed system employs machine learning techniques to perform multiclass classification and filtering important tweets with high degree of accuracy. The proposed system accurately flag tweets about injured or dead people, which we hope can expedite search and rescue efforts of concerned teams. Analysis of the results obtained indicates that efficiency of the system can be further enhanced by using appropriate deep learning techniques
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Omar, H., Sinha, A., Kumar, P. (2022). System for Situational Awareness Using Geospatial Twitter Data. In: Khanna, A., Gupta, D., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1394. Springer, Singapore. https://doi.org/10.1007/978-981-16-3071-2_59
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DOI: https://doi.org/10.1007/978-981-16-3071-2_59
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