@inproceedings{silva-etal-2025-cdb,
    title = "{CDB}: A Unified Framework for Hope Speech Detection Through Counterfactual, Desire and Belief",
    author = "Silva, Tulio Ferreira Leite Da  and
      Aduna, Gonzalo Freijedo  and
      Benamara, Farah  and
      Mari, Alda  and
      Li, Zongmin  and
      Yue, Li  and
      Su, Jian",
    editor = "Chiruzzo, Luis  and
      Ritter, Alan  and
      Wang, Lu",
    booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.findings-naacl.252/",
    pages = "4448--4463",
    ISBN = "979-8-89176-195-7",
    abstract = "Computational modeling of user-generated desires on social media can significantly aid decision-makers across various fields. Initially explored through wish speech,this task has evolved into a nuanced examination of hope speech. To enhance understanding and detection, we propose a novel scheme rooted in formal semantics approaches to modality, capturing both future-oriented hopes through desires and beliefs and the counterfactuality of past unfulfilled wishes and regrets. We manually re-annotated existing hope speech datasets and built a new one which constitutes a new benchmark in the field. We also explore the capabilities of LLMs in automatically detecting hope speech, relying on several prompting strategies. To the best of our knowledge, this is the first attempt towards a language-driven decomposition of the notional category hope and its automatic detection in a unified setting."
}