Intelligent and real-time alert model for disaster management based on information retrieval from multiple sources. (10th November 2020)

• Record Type: Journal Article
• Authors: Bouzidi, Zair; Amad, Mourad; Boudries, Abdelmalek
• Is Part Of: International journal of advanced media and communication. Volume 7:Number 4(2019)
• Page Start: 309
• Page End: 330
• Publication Date: 2020-11-10
• Subjects: disaster management -- social neworks -- annotated manually messages -- multiple sources (Twitter -- Facebook -- ) -- social media -- neural learning -- neural network-based alert system -- alert model -- intelligent and real-time alert model -- knowledge; Multimedia communications -- Periodicals; Multimedia systems -- Periodicals; 384.38
• Languages: English
• ISSNs: 1462-4613

Abstract

During the various catastrophic events of recent years, the use of social media to communicate timely information in crisis periods has become a common practice, allowing affected population to quickly publish a considerable amount of disaster information which can help managers making correct and quick decisions. In this paper, we propose a new real-time alert model for the management of natural or anthropogenic disasters. This model is based on a semi-supervised inductive technique to use unlabeled multi-source data, which are often abundant during a crisis event, with less data previously labeled than previous event. We use two sets of real-world crisis data from Facebook and Twitter manually tagged to launch streaming retrieval of relevant content: it is used for evaluating our proposed approach. Preliminary results are satisfactory.