@inproceedings{bungum-etal-2026-examination,
    title = "An Examination of the Party Leanings of Large Language Models",
    author = "Bungum, Lars  and
      Huang, Charles  and
      Bakken, Jari",
    editor = "Afli, Haithem  and
      Bouamor, Houda  and
      Zaghouani, Wajdi  and
      Ghannay, Sahar  and
      Hossain, Shehenaz",
    booktitle = "Proceedings of the 3rd Workshop on Natural Language Processing for Political Sciences ({P}olitical{NLP} 2026)",
    month = may,
    year = "2026",
    address = "Palma, Mallorca (Spain)",
    publisher = "ELRA Language Resources Association (ELRA)",
    url = "https://preview.aclanthology.org/test-year-match/2026.politicalnlp-1.21/",
    doi = "10.63317/2guhsurix7ke",
    pages = "195--203",
    abstract = "This paper examines the party leanings of international and Norwegian large language models. The experiments are two-fold; first they are asked to answer the question of a \textit{Valgomat}{--}an election affiliation guide{--}as a neutral observer, and secondly as if it were a paying party member of the parties in the data. Results show that the neutral prompting show centrist leanings, whereas models struggle with mimicking party members. Models with additional training on Norwegian text performed better on this task."
}