Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions

Pere-Lluís Huguet Cabot, David Abadi, Agneta Fischer, Ekaterina Shutova

Abstract
Computational modelling of political discourse tasks has become an increasingly important area of research in the field of natural language processing. Populist rhetoric has risen across the political sphere in recent years; however, due to its complex nature, computational approaches to it have been scarce. In this paper, we present the new Us vs. Them dataset, consisting of 6861 Reddit comments annotated for populist attitudes and the first large-scale computational models of this phenomenon. We investigate the relationship between populist mindsets and social groups, as well as a range of emotions typically associated with these. We set a baseline for two tasks associated with populist attitudes and present a set of multi-task learning models that leverage and demonstrate the importance of emotion and group identification as auxiliary tasks.
Anthology ID:
2021.eacl-main.165
Volume:
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Month:
April
Year:
2021
Address:
Online
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1921–1945
Language:
URL:
https://aclanthology.org/2021.eacl-main.165
DOI:
10.18653/v1/2021.eacl-main.165
Bibkey:
Cite (ACL):
Pere-Lluís Huguet Cabot, David Abadi, Agneta Fischer, and Ekaterina Shutova. 2021. Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 1921–1945, Online. Association for Computational Linguistics.
Cite (Informal):
Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions (Huguet Cabot et al., EACL 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/remove-xml-comments/2021.eacl-main.165.pdf
Code
 LittlePea13/UsVsThem
Data
Us Vs. Them
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