@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://aclanthology.org/2025.findings-naacl.252/",
doi = "10.18653/v1/2025.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."
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%0 Conference Proceedings
%T CDB: A Unified Framework for Hope Speech Detection Through Counterfactual, Desire and Belief
%A Silva, Tulio Ferreira Leite Da
%A Aduna, Gonzalo Freijedo
%A Benamara, Farah
%A Mari, Alda
%A Li, Zongmin
%A Yue, Li
%A Su, Jian
%Y Chiruzzo, Luis
%Y Ritter, Alan
%Y Wang, Lu
%S Findings of the Association for Computational Linguistics: NAACL 2025
%D 2025
%8 April
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-195-7
%F silva-etal-2025-cdb
%X 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.
%R 10.18653/v1/2025.findings-naacl.252
%U https://aclanthology.org/2025.findings-naacl.252/
%U https://doi.org/10.18653/v1/2025.findings-naacl.252
%P 4448-4463
Markdown (Informal)
[CDB: A Unified Framework for Hope Speech Detection Through Counterfactual, Desire and Belief](https://aclanthology.org/2025.findings-naacl.252/) (Silva et al., Findings 2025)
ACL
- Tulio Ferreira Leite Da Silva, Gonzalo Freijedo Aduna, Farah Benamara, Alda Mari, Zongmin Li, Li Yue, and Jian Su. 2025. CDB: A Unified Framework for Hope Speech Detection Through Counterfactual, Desire and Belief. In Findings of the Association for Computational Linguistics: NAACL 2025, pages 4448–4463, Albuquerque, New Mexico. Association for Computational Linguistics.