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Robust filtering of crisis-related tweets

Kersten, Jens and Kruspe, Anna and Wiegmann, Matti and Klan, Friederike (2019) Robust filtering of crisis-related tweets. In: ISCRAM 2019 Conference Proceedings - 16th International Conference on Information Systems for Crisis Response and Management. ISCRAM 2019, 2019-05-19 - 2019-05-22, Valencia, Spanien.

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Official URL: http://idl.iscram.org/files/jenskersten1/2019/1763_JensKersten1_etal2019.pdf


Social media enables fast information exchange and status reporting during crises. Filtering is usually required to identify the small fraction of social media stream data related to events. Since deep learning has recently shown to be a reliable approach for filtering and analyzing Twitter messages, a Convolutional Neural Network is examined for filtering crisis-related tweets in this work. The goal is to understand how to obtain accurate and robust filtering models and how model accuracies tend to behave in case of new events. In contrast to other works, the application to real data streams is also investigated. Motivated by the observation that machine learning model accuracies highly depend on the used data, a new comprehensive and balanced compilation of existing data sets is proposed.Experimental results with this data set provide valuable insights. Preliminary results from filtering a data stream recorded during hurricane Florence in September 2018 confirm our results.

Item URL in elib:https://elib.dlr.de/127586/
Document Type:Conference or Workshop Item (Speech)
Title:Robust filtering of crisis-related tweets
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Kersten, JensUNSPECIFIEDhttps://orcid.org/0000-0002-4735-7360UNSPECIFIED
Kruspe, AnnaUNSPECIFIEDhttps://orcid.org/0000-0002-2041-9453UNSPECIFIED
Wiegmann, MattiBauhaus-Universität WeimarUNSPECIFIEDUNSPECIFIED
Klan, FriederikeUNSPECIFIEDhttps://orcid.org/0000-0002-1856-7334UNSPECIFIED
Journal or Publication Title:ISCRAM 2019 Conference Proceedings - 16th International Conference on Information Systems for Crisis Response and Management
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
EditorsEmailEditor's ORCID iDORCID Put Code
Franco, Z.Medical College of WisconsinUNSPECIFIEDUNSPECIFIED
Canós, J. H.Universitat Politècnica de ValènciaUNSPECIFIEDUNSPECIFIED
Keywords:Filtering, Convolutional Neural Networks, Natural Disasters, Twitter, Model Transferability
Event Title:ISCRAM 2019
Event Location:Valencia, Spanien
Event Type:international Conference
Event Start Date:19 May 2019
Event End Date:22 May 2019
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:03 Jun 2019 11:45
Last Modified:24 Apr 2024 20:31

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