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- Publisher Website: 10.1080/12460125.2016.1187813
- Scopus: eid_2-s2.0-84976477543
- WOS: WOS:000378231800018
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Conference Paper: Risk-informed decisions for epidemics
Title | Risk-informed decisions for epidemics |
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Authors | |
Keywords | Risk-informed decisions Social media Epidemics Influenza-like illness |
Issue Date | 2016 |
Publisher | Taylor & Francis. The Journal's web site is located at http://www.tandfonline.com/tjds |
Citation | Proceedings of the 2016 Open Conference of the International Federation for Information Processing Working Group 8.3: Decision Support Systems (IFIP WG 8.3 DSS): Big Data, Better Decisions, Brighter Future, Cork, Ireland, 24-26 June 2016. In Journal of Decision Systems, 2016, v. 25 n. suppl.1, p. 240-247 How to Cite? |
Abstract | Social 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. |
Description | This journal suppl. entitled: Proceedings of the 2016 Open Conference of the IFIP WG 8.3 |
Persistent Identifier | http://hdl.handle.net/10722/235207 |
ISSN | 2023 Impact Factor: 2.8 2023 SCImago Journal Rankings: 0.746 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Feng, S | - |
dc.contributor.author | Hossain, L | - |
dc.date.accessioned | 2016-10-14T13:51:55Z | - |
dc.date.available | 2016-10-14T13:51:55Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Proceedings of the 2016 Open Conference of the International Federation for Information Processing Working Group 8.3: Decision Support Systems (IFIP WG 8.3 DSS): Big Data, Better Decisions, Brighter Future, Cork, Ireland, 24-26 June 2016. In Journal of Decision Systems, 2016, v. 25 n. suppl.1, p. 240-247 | - |
dc.identifier.issn | 1246-0125 | - |
dc.identifier.uri | http://hdl.handle.net/10722/235207 | - |
dc.description | This journal suppl. entitled: Proceedings of the 2016 Open Conference of the IFIP WG 8.3 | - |
dc.description.abstract | Social 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.language | eng | - |
dc.publisher | Taylor & Francis. The Journal's web site is located at http://www.tandfonline.com/tjds | - |
dc.relation.ispartof | Journal of Decision Systems | - |
dc.subject | Risk-informed decisions | - |
dc.subject | Social media | - |
dc.subject | Epidemics | - |
dc.subject | Influenza-like illness | - |
dc.title | Risk-informed decisions for epidemics | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Hossain, L: lhossain@hku.hk | - |
dc.identifier.authority | Hossain, L=rp01858 | - |
dc.description.nature | link_to_OA_fulltext | - |
dc.identifier.doi | 10.1080/12460125.2016.1187813 | - |
dc.identifier.scopus | eid_2-s2.0-84976477543 | - |
dc.identifier.hkuros | 267933 | - |
dc.identifier.hkuros | 267294 | - |
dc.identifier.hkuros | 302118 | - |
dc.identifier.hkuros | 302122 | - |
dc.identifier.volume | 25 | - |
dc.identifier.issue | suppl.1 | - |
dc.identifier.spage | 240 | - |
dc.identifier.epage | 247 | - |
dc.identifier.isi | WOS:000378231800018 | - |
dc.publisher.place | United Kingdom | - |
dc.customcontrol.immutable | sml 161124 | - |
dc.identifier.issnl | 1246-0125 | - |