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DisDSS: a novel Web-based smart disaster management system for determining the nature of a social media message for decision-making using deep learning – case study of COVID-19

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Publicado en:Global Knowledge, Memory and Communication vol. 73, no. 8/9 (2024), p. 1044-1065
Autor principal: Singla, Annie
Otros Autores: Agrawal, Rajat
Publicado:
Emerald Group Publishing Limited
Materias:
Ushahidi
Earthquakes
Datasets
Coronaviruses
Social networks
COVID-19
Social media
Deep learning
Case studies
Literature
Novels
Recall
Bidirectionality
Decision making
Disaster management
Disasters
Learning
Short term memory
Neural networks
Mass media
Computerized decision support systems
Acceso en línea:Citation/Abstract
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Resumen:PurposeThis paper aims to propose DisDSS: a Web-based smart disaster management (DM) system for decision-making that will assist disaster professionals in determining the nature of disaster-related social media (SM) messages. The research classifies the tweets into need-based, availability-based, situational-based, general and irrelevant categories and visualizes them on a web interface, location-wise.Design/methodology/approachIt is worth mentioning that a fusion-based deep learning (DL) model is introduced to objectively determine the nature of an SM message. The proposed model uses the convolution neural network and bidirectional long short-term memory network layers.FindingsThe developed system leads to a better performance in accuracy, precision, recall, F-score, area under receiver operating characteristic curve and area under precision-recall curve, compared to other state-of-the-art methods in the literature. The contribution of this paper is three fold. First, it presents a new covid data set of SM messages with the label of nature of the message. Second, it offers a fusion-based DL model to classify SM data. Third, it presents a Web-based interface to visualize the structured information.Originality/valueThe architecture of DisDSS is analyzed based on the practical case study, i.e. COVID-19. The proposed DL-based model is embedded into a Web-based interface for decision support. To the best of the authors’ knowledge, this is India’s first SM-based DM system.
ISSN:2514-9342
2514-9350
0024-2535
1758-793X
DOI:10.1108/GKMC-07-2022-0180
Fuente:Library Science Database