COLING 2025main0 citations

CharMoral: A Character Morality Dataset for Morally Dynamic Character Analysis in Long-Form Narratives

Suyoung Bae, Gunhee Cho, Yun-Gyung Cheong, Boyang Li

Abstract

This paper introduces CharMoral, a dataset designed to analyze the moral evolution of characters in long-form narratives. CharMoral, built from 1,337 movie synopses, includes annotations for character actions, context, and morality labels. To automatically construct CharMoral, we propose a four-stage framework, utilizing Large Language Models, to automatically classify actions as moral or immoral based on context. Human evaluations and various experiments confirm the framework’s effectiveness in moral reasoning tasks in multiple genres. Our code and the CharMoral dataset are publicly available at https://github.com/BaeSuyoung/CharMoral.

BibTeX
@inproceedings{bae-etal-2025-charmoral,
    title = "{C}har{M}oral: A Character Morality Dataset for Morally Dynamic Character Analysis in Long-Form Narratives",
    author = "Bae, Suyoung  and
      Cho, Gunhee  and
      Cheong, Yun-Gyung  and
      Li, Boyang",
    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://aclanthology.org/2025.coling-main.589/",
    pages = "8809--8818"
}
CharMoral: A Character Morality Dataset for Morally Dynamic Character Analysis in Long-Form Narratives · COLING 2025