Using spatiotemporal distribution of geocoded Twitter data to predict US county-level health indices

Nguyen, Thin, Larsen, Mark, O'Dea, Bridianne, Nguyen, Hung, Nguyen, Duc Thanh, Yearwood, John, Phung, Dinh, Venkatesh, Svetha and Christensen, Helen 2018, Using spatiotemporal distribution of geocoded Twitter data to predict US county-level health indices, Future generation computer systems, pp. 1-9, doi: 10.1016/j.future.2018.01.014.

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Title Using spatiotemporal distribution of geocoded Twitter data to predict US county-level health indices
Author(s) Nguyen, ThinORCID iD for Nguyen, Thin orcid.org/0000-0003-3467-8963
Larsen, Mark
O'Dea, Bridianne
Nguyen, Hung
Nguyen, Duc Thanh
Yearwood, JohnORCID iD for Yearwood, John orcid.org/0000-0002-7562-6767
Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Christensen, Helen
Journal name Future generation computer systems
Start page 1
End page 9
Total pages 9
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2018
ISSN 0167-739X
Keyword(s) Mining spatial and temporal data
Statistical features
Spatio-temporal features
Cluster computing
Large-scale parallel and distributed implementation
Apache Spark
Notes In press
Language eng
DOI 10.1016/j.future.2018.01.014
Indigenous content off
Field of Research 0805 Distributed Computing
0806 Information Systems
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2018, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30111467

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