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short-paper

Development of Failure Detection System for Network Control using Collective Intelligence of Social Networking Service in Large-Scale Disasters

Authors:

Saneyasu Yamaguchi,

Masato OguchiAuthors Info & Claims

HT '16: Proceedings of the 27th ACM Conference on Hypertext and Social Media

Pages 267 - 272

https://doi.org/10.1145/2914586.2914620

Published: 10 July 2016 Publication History

Abstract

When the Great East Japan Earthquake occurred in 2011, it was difficult to immediately grasp all telecommunications network conditions using only information from network monitoring devices because the damage was considerably heavy and a severe congestion control state occurred. Moreover, at the time of the earthquake, telephone and e-mail services could not be used in many cases-although social networking services (SNSs) were still available. In an emergency, such as an earthquake, users proactively convey information on telecommunications network conditions through SNSs. Therefore the collective intelligence of SNSs is suitable as a means of information detection complementary to conventional observation through network monitoring devices. In this paper, we propose a network failure detection system that detects telephony failures with a high degree of accuracy by using the collective intelligence of Twitter, one of the most widely used SNSs. We also show that network control can be performed automatically and autonomically using information on telecommunications network conditions detected with our system.

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Cited By

Pal AWang JWu YKant KLiu ZSato K(2023)Social Media Driven Big Data Analysis for Disaster Situation Awareness: A TutorialIEEE Transactions on Big Data10.1109/TBDATA.2022.31584319:1(1-21)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TBDATA.2022.3158431
Maru CEnoki MNakao AYamamoto SYamaguchi SOguchi M(2016)QoE Control of Network Using Collective Intelligence of SNS in Large-Scale Disasters2016 IEEE International Conference on Computer and Information Technology (CIT)10.1109/CIT.2016.68(57-64)Online publication date: Dec-2016
https://doi.org/10.1109/CIT.2016.68

Index Terms

Development of Failure Detection System for Network Control using Collective Intelligence of Social Networking Service in Large-Scale Disasters

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Published In

cover image ACM Conferences

HT '16: Proceedings of the 27th ACM Conference on Hypertext and Social Media

July 2016

354 pages

ISBN:9781450342476

DOI:10.1145/2914586

General Chairs:
Jamie Blustein
Dalhousie University, Canada
,
Eelco Herder
L3S Research Center, Germany
,
Program Chairs:
Jessica Rubart
OWL University of Applied Sciences, Germany
,
Helen Ashman
University of South Australia

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 July 2016

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HT '16: 27th ACM Conference on Hypertext and Social Media

July 10 - 13, 2016

Nova Scotia, Halifax, Canada

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HT '16 Paper Acceptance Rate 16 of 54 submissions, 30%;

Overall Acceptance Rate 378 of 1,158 submissions, 33%

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Cited By

Pal AWang JWu YKant KLiu ZSato K(2023)Social Media Driven Big Data Analysis for Disaster Situation Awareness: A TutorialIEEE Transactions on Big Data10.1109/TBDATA.2022.31584319:1(1-21)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TBDATA.2022.3158431
Maru CEnoki MNakao AYamamoto SYamaguchi SOguchi M(2016)QoE Control of Network Using Collective Intelligence of SNS in Large-Scale Disasters2016 IEEE International Conference on Computer and Information Technology (CIT)10.1109/CIT.2016.68(57-64)Online publication date: Dec-2016
https://doi.org/10.1109/CIT.2016.68

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