Crossmark

Identifying disaster-related tweets and their semantic, spatial and temporal context using deep learning, natural language processing and spatial analysis: a case study of Hurricane Irma

Crossref DOI link: https://doi.org/10.1080/17538947.2018.1563219

Published Online: 2019-01-03

Published Print: 2019-11-02

Update policy: https://doi.org/10.1080/tandf_crossmark_01

Authors

Sit, Muhammed Ali http://orcid.org/0000-0002-2707-6692
Koylu, Caglar http://orcid.org/0000-0001-6619-6366
Demir, Ibrahim http://orcid.org/0000-0002-0461-1242
More Information

Peer Review Statement: The publishing and review policy for this title is described in its Aims & Scope.

Aim & Scope: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=tjde20

Publication History

Received: 2018-05-08

Accepted: 2018-12-20

Published: 2019-01-03

Document is current

Any future updates will be listed below