Crowdsourcing-based timeline description of urban emergency events using social media

Xu, Z; Zhang, H; Hu, C; Liu, Y; Xuan, J; Mei, L

Crowdsourcing-based timeline description of urban emergency events using social media

Xu, Z Zhang, H Hu, C Liu, Y Xuan, J

Mei, L

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Publisher:: Inderscience
Publication Type:: Journal Article
Citation:: International Journal of Ad Hoc and Ubiquitous Computing, 2017, 25, (1-2), pp. 41-51
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	Xu, Z
dc.contributor.author	Zhang, H
dc.contributor.author	Hu, C
dc.contributor.author	Liu, Y
dc.contributor.author	Xuan, J https://orcid.org/0000-0002-8367-6908
dc.contributor.author	Mei, L
dc.date.accessioned	2022-08-11T05:02:40Z
dc.date.available	2022-08-11T05:02:40Z
dc.date.issued	2017-01-01
dc.identifier.citation	International Journal of Ad Hoc and Ubiquitous Computing, 2017, 25, (1-2), pp. 41-51
dc.identifier.issn	1743-8225
dc.identifier.issn	1743-8233
dc.identifier.uri	http://hdl.handle.net/10453/159931
dc.description.abstract	Crowdsourcing is a newly emerging service platform and business model in the Internet. Analysis and description about urban emergency events, e.g., fires, storms and traffic jams are of great importance to protect the security of humans. Recently, social media feeds are rapidly emerging as a novel platform for providing and dissemination of information that is often geographic. In this paper, in order to describe the timeline of real-time urban emergency events, the new web mining task timeline description (TD) is proposed. Firstly, the related information of an urban emergency event is extracted from Weibo messages. Secondly, the valid message including the semantic or spatial information is detected in this step. Thirdly, detected valid messages are used to build the TD. Case studies on real datasets show the proposed model has good performance and high effectiveness in the analysis and description of urban emergency events.
dc.language	English
dc.publisher	Inderscience
dc.relation.ispartof	International Journal of Ad Hoc and Ubiquitous Computing
dc.relation.isbasedon	10.1504/IJAHUC.2017.083481
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0805 Distributed Computing, 1005 Communications Technologies, 1702 Cognitive Sciences
dc.subject.classification	Networking & Telecommunications
dc.title	Crowdsourcing-based timeline description of urban emergency events using social media
dc.type	Journal Article
utslib.citation.volume	25
utslib.for	0805 Distributed Computing
utslib.for	1005 Communications Technologies
utslib.for	1702 Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-08-11T05:02:38Z
pubs.issue	1-2
pubs.publication-status	Published
pubs.volume	25
utslib.citation.issue	1-2

Abstract:

Crowdsourcing is a newly emerging service platform and business model in the Internet. Analysis and description about urban emergency events, e.g., fires, storms and traffic jams are of great importance to protect the security of humans. Recently, social media feeds are rapidly emerging as a novel platform for providing and dissemination of information that is often geographic. In this paper, in order to describe the timeline of real-time urban emergency events, the new web mining task timeline description (TD) is proposed. Firstly, the related information of an urban emergency event is extracted from Weibo messages. Secondly, the valid message including the semantic or spatial information is detected in this step. Thirdly, detected valid messages are used to build the TD. Case studies on real datasets show the proposed model has good performance and high effectiveness in the analysis and description of urban emergency events.

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http://hdl.handle.net/10453/159931