@inproceedings{caporusso-etal-2024-computational,
    title = "A Computational Analysis of the Dehumanisation of Migrants from Syria and {U}kraine in {S}lovene News Media",
    author = "Caporusso, Jaya  and
      Hoogland, Damar  and
      Brglez, Mojca  and
      Koloski, Boshko  and
      Purver, Matthew  and
      Pollak, Senja",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.18",
    pages = "199--210",
    abstract = "Dehumanisation involves the perception and/or treatment of a social group{'}s members as less than human. This phenomenon is rarely addressed with computational linguistic techniques. We adapt a recently proposed approach for English, making it easier to transfer to other languages and to evaluate, introducing a new sentiment resource, the use of zero-shot cross-lingual valence and arousal detection, and a new method for statistical significance testing. We then apply it to study attitudes to migration expressed in Slovene newspapers, to examine changes in the Slovene discourse on migration between the 2015-16 migration crisis following the war in Syria and the 2022-23 period following the war in Ukraine. We find that while this discourse became more negative and more intense over time, it is less dehumanising when specifically addressing Ukrainian migrants compared to others.",
}

Dehumanisation involves the perception and/or treatment of a social group{'}s members as less than human. This phenomenon is rarely addressed with computational linguistic techniques. We adapt a recently proposed approach for English, making it easier to transfer to other languages and to evaluate, introducing a new sentiment resource, the use of zero-shot cross-lingual valence and arousal detection, and a new method for statistical significance testing. We then apply it to study attitudes to migration expressed in Slovene newspapers, to examine changes in the Slovene discourse on migration between the 2015-16 migration crisis following the war in Syria and the 2022-23 period following the war in Ukraine. We find that while this discourse became more negative and more intense over time, it is less dehumanising when specifically addressing Ukrainian migrants compared to others.
Caporusso, Jaya Hoogl , Damar Brglez, Mojca Koloski, Boshko Purver, Matthew Pollak, Senja
A Computational Analysis of the Dehumanisation of Migrants from Syria and Ukraine in Slovene News Media