Disaster Tweet Corpus 2020

Wiegmann, Matti and Kersten, Jens and Klan, Friederike and Potthast, Martin and Stein, Benno (2020) Disaster Tweet Corpus 2020. [Other]

Full text not available from this repository.

Official URL: https://zenodo.org/record/3713920

Abstract

This dataset consists of tweets collected during 48 disasters over 10 disaster types with human annotations denoting if a tweet is related to this disaster or not. This collection is intended as a benchmarking dataset for filtering algorithms.

Item URL in elib:

https://elib.dlr.de/140113/

Document Type:

Other

Title:

Disaster Tweet Corpus 2020

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Wiegmann, Matti	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Kersten, Jens	UNSPECIFIED	https://orcid.org/0000-0002-4735-7360	UNSPECIFIED
Klan, Friederike	UNSPECIFIED	https://orcid.org/0000-0002-1856-7334	UNSPECIFIED
Potthast, Martin	Leipzig University	UNSPECIFIED	UNSPECIFIED
Stein, Benno	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED

Date:

2020

Journal or Publication Title:

Disaster Tweet Corpus 2020 [Data Set]

Refereed publication:

Open Access:

DOI:

10.5281/zenodo.3713920

Status:

Published

Keywords:

data set, Twitter, disasters, disaster-relatedness

HGF - Research field:

Aeronautics, Space and Transport

HGF - Program:

Space

HGF - Program Themes:

other

DLR - Research area:

Raumfahrt

DLR - Program:

R - no assignment

DLR - Research theme (Project):

R - no assignment

Location:

Jena

Institutes and Institutions:

Institute of Data Science > Citizen Science

Deposited By:

Kersten, Dr.-Ing. Jens

Deposited On:

07 Jan 2021 07:52

Last Modified:

07 Jan 2021 07:52

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