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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:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Wiegmann, MattiMatti.Wiegmann (at) dlr.deUNSPECIFIED
Kersten, Jensjens.kersten (at) dlr.dehttps://orcid.org/0000-0002-4735-7360
Klan, FriederikeFriederike.Klan (at) dlr.dehttps://orcid.org/0000-0002-1856-7334
Potthast, MartinLeipzig UniversityUNSPECIFIED
Stein, Bennobenno.stein (at) uni-weimar.deUNSPECIFIED
Date:2020
Journal or Publication Title:Disaster Tweet Corpus 2020 [Data Set]
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
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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