A Dataset for the Detection of Dehumanizing Language

Paul Engelmann, Peter Trolle, Christian Hardmeier


Abstract
Dehumanization is a mental process that enables the exclusion and ill treatment of a group of people. In this paper, we present two data sets of dehumanizing text, a large, automatically collected corpus and a smaller, manually annotated data set. Both data sets include a combination of political discourse and dialogue from movie subtitles. Our methods give us a broad and varied amount of dehumanization data to work with, enabling further exploratory analysis as well as automatic classification of dehumanization patterns. Both data sets will be publicly released.
Anthology ID:
2024.ltedi-1.2
Volume:
Proceedings of the Fourth Workshop on Language Technology for Equality, Diversity, Inclusion
Month:
March
Year:
2024
Address:
St. Julian's, Malta
Editors:
Bharathi Raja Chakravarthi, Bharathi B, Paul Buitelaar, Thenmozhi Durairaj, György Kovács, Miguel Ángel García Cumbreras
Venues:
LTEDI | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
14–20
Language:
URL:
https://aclanthology.org/2024.ltedi-1.2
DOI:
Bibkey:
Cite (ACL):
Paul Engelmann, Peter Trolle, and Christian Hardmeier. 2024. A Dataset for the Detection of Dehumanizing Language. In Proceedings of the Fourth Workshop on Language Technology for Equality, Diversity, Inclusion, pages 14–20, St. Julian's, Malta. Association for Computational Linguistics.
Cite (Informal):
A Dataset for the Detection of Dehumanizing Language (Engelmann et al., LTEDI-WS 2024)
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