@inproceedings{klamm-etal-2023-kind,
    title = "Our kind of people? Detecting populist references in political debates",
    author = "Klamm, Christopher  and
      Rehbein, Ines  and
      Ponzetto, Simone Paolo",
    editor = "Vlachos, Andreas  and
      Augenstein, Isabelle",
    booktitle = "Findings of the Association for Computational Linguistics: EACL 2023",
    month = may,
    year = "2023",
    address = "Dubrovnik, Croatia",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2023.findings-eacl.91/",
    doi = "10.18653/v1/2023.findings-eacl.91",
    pages = "1227--1243",
    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."
}