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Information Overload in Crisis Management: Bilingual Evaluation of Embedding Models for Clustering Social Media Posts in Emergencies

Bayer, Markus ; Kaufhold, Marc-André ; Reuter, Christian (2022):
Information Overload in Crisis Management: Bilingual Evaluation of Embedding Models for Clustering Social Media Posts in Emergencies. (Publisher's Version)
In: ECIS 2021 Research Papers, In: ECIS 2021 Research-in-Progress Papers,
Darmstadt, AIS, European Conference on Information Systems (ECIS 2021), Marrakech, Morocco, 14.-16.06.2021, ISBN 978-1-7336325-6-0,
DOI: 10.26083/tuprints-00022167,
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Status: Publisher's Version
Title: Information Overload in Crisis Management: Bilingual Evaluation of Embedding Models for Clustering Social Media Posts in Emergencies
Language: English
Abstract:

Past studies in the domains of information systems have analysed the potentials and barriers of social media in emergencies. While information disseminated in social media can lead to valuable insights, emergency services and researchers face the challenge of information overload as data quickly exceeds the manageable amount. We propose an embedding-based clustering approach and a method for the automated labelling of clusters. Given that the clustering quality is highly dependent on embeddings, we evaluate 19 embedding models with respect to time, internal cluster quality, and language invariance. The results show that it may be sensible to use embedding models that were already trained on other crisis datasets. However, one must ensure that the training data generalizes enough, so that the clustering can adapt to new situations. Confirming this, we found out that some embeddings were not able to perform as well on a German dataset as on an English dataset.

Book Title: ECIS 2021 Research-in-Progress Papers
Series: ECIS 2021 Research Papers
Place of Publication: Darmstadt
Publisher: AIS
Collation: 18 Seiten
Uncontrolled Keywords: Social Media Clustering, Information Overload, Crisis Informatics, Unsupervised Machine Learning
Classification DDC: 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
000 Allgemeines, Informatik, Informationswissenschaft > 070 Nachrichtenmedien, Journalismus, Verlagswesen
Divisions: 20 Department of Computer Science > Science and Technology for Peace and Security (PEASEC)
Forschungsfelder > Information and Intelligence > Cybersecurity & Privacy
Event Title: European Conference on Information Systems (ECIS 2021)
Event Location: Marrakech, Morocco
Event Dates: 14.-16.06.2021
Date Deposited: 05 Sep 2022 13:38
Last Modified: 05 Sep 2022 13:38
DOI: 10.26083/tuprints-00022167
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-221672
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/22167
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