A social media-based over layer on the edge for handling emergency-related events. (December 2021)

• Record Type: Journal Article
• Authors: Tundis, Andrea; Melnik, Maksim; Naveed, Hashim; Mühlhäuser, Max
• Is Part Of: Computers & electrical engineering. Volume 96:Part B(2021)
• Publication Date: 2021-12
• Subjects: Internet of Things -- Online social networks -- Text mining -- Machine learning -- Safety -- Crime detection -- Emergency management; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2021.107570
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Online Social Networks (OSNs), together with messaging services are tools for the exchange of entertainment-related information. However, they represent virtual environments capable of providing relevant information related to emergency or criminal events. Thanks to the simple way of using OSNs in combination to modern ubiquitous Internet of Things (IoT) smart devices, the generation and exploitation of such information is made available to users in real-time even more easily. Unfortunately, its reuse has not been taken into consideration yet due to the lack of specific models and related software tools. In this context, the paper presents a social media-based over layer for supporting the monitoring, detection, computation and information sharing of social media information related to emergency scenarios centered on smartphones and text mining techniques. The proposal is assessed through two different case studies, by evaluating the performances of different classifiers and by showing the logic of the functionalities of the related apps.