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Conference Paper: Risk-informed decision for epidemics

TitleRisk-informed decision for epidemics
Authors
KeywordsRisk-informed decisions
Social media
Epidemics
Influenza-like illness
Issue Date2016
PublisherTaylor & Francis. The Journal's web site is located at http://www.tandfonline.com/tjds
Citation
The 2016 Open Conference of the IFIP WG 8.3, Cork, Ireland, 22-24 june 2016. In Conference Proceedings, 2016, v. 25 n. S1, p. 240-247 How to Cite?
AbstractSocial media, an open and free platform containing large volume of user-generated content (UGC) is an ideal data source to achieve risk-informed decisions for epidemics. The probability and predictive value of how social systems deal with epidemics can be conceptually and empirically studied by monitoring social media data for formulating risk-informed decisions in improving preparedness and response to epidemics. ILI (influenza-like illness) surveillance by monitoring social media data offers opportunity to provide early warning signs for improving public health interventions. In this research, we monitored Weibo, a Chinese social media data on swine flu in 2011 to analyse the post content, the correlation with official surveillance data as well as geography distribution in order to verify whether Weibo is an effective platform for conducting risk-informed decision for epidemics.
DescriptionConference Theme: Big Data, Better Decisions, Brighter Future
This journal suppl. entitled: Proceedings of the 2016 Open Conference of the IFIP WG 8.3
Persistent Identifierhttp://hdl.handle.net/10722/235207
ISSN
2015 SCImago Journal Rankings: 0.272

 

DC FieldValueLanguage
dc.contributor.authorFeng, S-
dc.contributor.authorHossain, L-
dc.date.accessioned2016-10-14T13:51:55Z-
dc.date.available2016-10-14T13:51:55Z-
dc.date.issued2016-
dc.identifier.citationThe 2016 Open Conference of the IFIP WG 8.3, Cork, Ireland, 22-24 june 2016. In Conference Proceedings, 2016, v. 25 n. S1, p. 240-247-
dc.identifier.issn1246-0125-
dc.identifier.urihttp://hdl.handle.net/10722/235207-
dc.descriptionConference Theme: Big Data, Better Decisions, Brighter Future-
dc.descriptionThis journal suppl. entitled: Proceedings of the 2016 Open Conference of the IFIP WG 8.3-
dc.description.abstractSocial media, an open and free platform containing large volume of user-generated content (UGC) is an ideal data source to achieve risk-informed decisions for epidemics. The probability and predictive value of how social systems deal with epidemics can be conceptually and empirically studied by monitoring social media data for formulating risk-informed decisions in improving preparedness and response to epidemics. ILI (influenza-like illness) surveillance by monitoring social media data offers opportunity to provide early warning signs for improving public health interventions. In this research, we monitored Weibo, a Chinese social media data on swine flu in 2011 to analyse the post content, the correlation with official surveillance data as well as geography distribution in order to verify whether Weibo is an effective platform for conducting risk-informed decision for epidemics.-
dc.languageeng-
dc.publisherTaylor & Francis. The Journal's web site is located at http://www.tandfonline.com/tjds-
dc.relation.ispartofJournal of Decision Systems-
dc.subjectRisk-informed decisions-
dc.subjectSocial media-
dc.subjectEpidemics-
dc.subjectInfluenza-like illness-
dc.titleRisk-informed decision for epidemics-
dc.typeConference_Paper-
dc.identifier.emailHossain, L: lhossain@hku.hk-
dc.identifier.authorityHossain, L=rp01858-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1080/12460125.2016.1187813-
dc.identifier.scopuseid_2-s2.0-84976477543-
dc.identifier.hkuros267933-
dc.identifier.volume25-
dc.identifier.issuesuppl. S1-
dc.identifier.spage240-
dc.identifier.epage247-
dc.publisher.placeUnited Kingdom-
dc.customcontrol.immutablesml 161124-

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