Combining machine-learning topic models and spatiotemporal analysis of social media data for disaste...
Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment
About this item
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Author / Creator
Publisher
Taylor & Francis
Journal title
Language
English
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Publisher
Taylor & Francis
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Scope and Contents
Contents
Current disaster management procedures to cope with human and economic losses and to manage a disaster's aftermath suffer from a number of shortcomings like high temporal lags or limited temporal and spatial resolution. This paper presents an approach to analyze social media posts to assess the footprint of and the damage caused by natural disaster...
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Full title
Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_crossref_primary_10_1080_15230406_2017_1356242
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_primary_10_1080_15230406_2017_1356242
Other Identifiers
ISSN
1523-0406
E-ISSN
1545-0465
DOI
10.1080/15230406.2017.1356242
