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A social media-based over layer on the edge for handling emergency-related events

Tundis, Andrea ; Melnik, Maksim ; Naveed, Hashim ; Mühlhäuser, Max (2021):
A social media-based over layer on the edge for handling emergency-related events.
In: Computers & Electrical Engineering, 96 (Part B), Elsevier, ISSN 0045-7906,
DOI: 10.1016/j.compeleceng.2021.107570,
[Article]

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.

Item Type: Article
Erschienen: 2021
Creators: Tundis, Andrea ; Melnik, Maksim ; Naveed, Hashim ; Mühlhäuser, Max
Title: A social media-based over layer on the edge for handling emergency-related events
Language: English
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.

Journal or Publication Title: Computers & Electrical Engineering
Journal volume: 96
Number: Part B
Publisher: Elsevier
Uncontrolled Keywords: Internet of Things, Online social networks, Text mining, Machine learning, Safety, Crime detection, Emergency management
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Telecooperation
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > emergenCITY
Date Deposited: 21 Dec 2021 11:55
DOI: 10.1016/j.compeleceng.2021.107570
Official URL: https://www.sciencedirect.com/science/article/pii/S004579062...
Additional Information:

Art.No.: 107570

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