Kernel-based features for predicting population health indices from geocoded social media data

Nguyen, Thin, Larsen, Mark E., O'Dea, Bridianne, Nguyen, Duc Thanh, Yearwood, John Leighton, Phung, Quoc-Dinh, Venkatesh, Svetha and Christensen, Helen 2017, Kernel-based features for predicting population health indices from geocoded social media data, Decision Support Systems, vol. 102, pp. 22-31, doi: 10.1016/j.dss.2017.06.010.

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Title Kernel-based features for predicting population health indices from geocoded social media data
Author(s) Nguyen, ThinORCID iD for Nguyen, Thin orcid.org/0000-0003-3467-8963
Larsen, Mark E.
O'Dea, Bridianne
Nguyen, Duc Thanh
Yearwood, John LeightonORCID iD for Yearwood, John Leighton orcid.org/0000-0002-7562-6767
Phung, Quoc-DinhORCID iD for Phung, Quoc-Dinh orcid.org/0000-0002-9977-8247
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Christensen, Helen
Journal name Decision Support Systems
Volume number 102
Start page 22
End page 31
Total pages 10
Publisher Elsevier BV
Place of publication Amsterdam, The Netherlands
Publication date 2017-10-01
ISSN 0167-9236
Keyword(s) spatial decision support system
georeferenced social media
spatial big data
health rankings
Twitter
kernel function
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Information Systems
Operations Research & Management Science
Computer Science
VOLUNTEERED GEOGRAPHIC INFORMATION
DECISION-SUPPORT-SYSTEM
SENTIMENT ANALYSIS
TWEETS
SURVEILLANCE
MANAGEMENT
NETWORKS
FACEBOOK
Language eng
DOI 10.1016/j.dss.2017.06.010
Field of Research 0804 Data Format
0805 Distributed Computing
01 MATHEMATICAL SCIENCES
08 INFORMATION AND COMPUTING SCIENCES
15 COMMERCE, MANAGEMENT, TOURISM AND SERVICES
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2017, Elsevier B.V.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30100695

Document type: Journal Article
Collection: School of Information Technology
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