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Classification of Incident-related Tweets: Exploiting Word and Sentence Embeddings

Kruspe, Anna and Kersten, Jens and Klan, Friederike (2019) Classification of Incident-related Tweets: Exploiting Word and Sentence Embeddings. Text REtrieval Conference (TREC), 13-15 Nov 2019, Gaithersburg, USA.

Full text not available from this repository.

Abstract

In this paper, we present our five approaches submitted to the Text REtrieval Conference (TREC) Incident Streams (IS) 2019B edition. The goal is to classify crisis-related tweets into a variable set of information classes and to provide an importance score. This multi-class, multi-label and multi-task problem turns out to be even more challenging because of extremely unbalanced training data available. We use recently proposed, publicy available word and sentence embeddings and deep neural network models for this task.

Item URL in elib:https://elib.dlr.de/133224/
Document Type:Conference or Workshop Item (Speech, Poster)
Title:Classification of Incident-related Tweets: Exploiting Word and Sentence Embeddings
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Kruspe, Annaanna.kruspe (at) dlr.dehttps://orcid.org/0000-0002-2041-9453
Kersten, Jensjens.kersten (at) dlr.dehttps://orcid.org/0000-0002-4735-7360
Klan, FriederikeFriederike.Klan (at) dlr.dehttps://orcid.org/0000-0002-1856-7334
Date:2019
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Accepted
Keywords:social media, tweet, classification, disaster management
Event Title:Text REtrieval Conference (TREC)
Event Location:Gaithersburg, USA
Event Type:international Conference
Event Dates:13-15 Nov 2019
Organizer:NIST
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 2020 14:43
Last Modified:07 Jan 2020 14:43

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