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
- Editors:
- Paola Merlo, Jorg Tiedemann, Reut Tsarfaty
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2021.eacl-main.165.pdf
- Code
- LittlePea13/UsVsThem
- Data
- Us Vs. Them