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 (original) (raw)

Global Knowledge, Memory and Communication

Abstract

Purpose This 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/approach It 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. Findings The 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 prese...

Rajat Agrawal hasn't uploaded this paper.

Let Rajat know you want this paper to be uploaded.

Ask for this paper to be uploaded.