@inproceedings{vallejo-etal-2025-human,
    title = "Human Interest Framing across Cultures: A Case Study on Climate Change",
    author = "Vallejo, Gisela  and
      de Kock, Christine  and
      Baldwin, Timothy  and
      Frermann, Lea",
    editor = "Rambow, Owen  and
      Wanner, Leo  and
      Apidianaki, Marianna  and
      Al-Khalifa, Hend  and
      Eugenio, Barbara Di  and
      Schockaert, Steven",
    booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
    month = jan,
    year = "2025",
    address = "Abu Dhabi, UAE",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.coling-main.754/",
    pages = "11380--11398",
    abstract = "Human Interest (HI) framing is a narrative strategy that injects news stories with a relatable, emotional angle and a human face to engage the audience. In this study we investigate the use of HI framing across different English-speaking cultures in news articles about climate change. Despite its demonstrated impact on the public{'}s behaviour and perception of an issue, HI framing has been under-explored in NLP to date. We perform a systematic analysis of HI stories to understand its role in climate change reporting in English-speaking countries from four continents. Our findings reveal key differences in how climate change is portrayed across countries, encompassing aspects such as narrative roles, article polarity, pronoun prevalence, and topics. We also demonstrate that these linguistic aspects boost the performance of fine-tuned pre-trained language models on HI story classification."
}