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 data. 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.
CITATION STYLE
Klamm, C., Rehbein, I., & Ponzetto, S. P. (2023). Our kind of people? Detecting populist references in political debates. In EACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2023 (pp. 1197–1213). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.findings-eacl.91
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