Abstract
This paper investigates the identification of populist rhetoric in text and presents a novel cross-lingual dataset for this task. Our work is based on the definition of populism as a “communication style of political actors that refers to the people” but also includes anti-elitism as another core feature of populism. Accordingly, we annotate references to The People and The Elite in German and English parliamentary debates with a hierarchical scheme. The paper describes our dataset and annotation procedure and reports inter-annotator agreement for this task. Next, we compare and evaluate different transformer-based model architectures on a German dataset and report results for zero-shot learning on a smaller English dataset. We then show that semi-supervised tri-training can improve results in the cross-lingual setting. Our dataset can be used to investigate how political actors talk about The Elite and The People and to study how populist rhetoric is used as a strategic device.- Anthology ID:
- 2023.findings-eacl.91
- Volume:
- Findings of the Association for Computational Linguistics: EACL 2023
- Month:
- May
- Year:
- 2023
- Address:
- Dubrovnik, Croatia
- Editors:
- Andreas Vlachos, Isabelle Augenstein
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1227–1243
- Language:
- URL:
- https://aclanthology.org/2023.findings-eacl.91
- DOI:
- 10.18653/v1/2023.findings-eacl.91
- Cite (ACL):
- Christopher Klamm, Ines Rehbein, and Simone Paolo Ponzetto. 2023. Our kind of people? Detecting populist references in political debates. In Findings of the Association for Computational Linguistics: EACL 2023, pages 1227–1243, Dubrovnik, Croatia. Association for Computational Linguistics.
- Cite (Informal):
- Our kind of people? Detecting populist references in political debates (Klamm et al., Findings 2023)
- PDF:
- https://preview.aclanthology.org/landing_page/2023.findings-eacl.91.pdf