ME2-BERT: Are Events and Emotions what you need for Moral Foundation Prediction?
Lorenzo Zangari, Candida M. Greco, Davide Picca, Andrea Tagarelli
Abstract
Moralities, emotions, and events are complex aspects of human cognition, which are often treated separately since capturing their combined effects is challenging, especially due to the lack of annotated data. Leveraging their interrelations hence becomes crucial for advancing the understanding of human moral behaviors. In this work, we propose ME2-BERT, the first holistic framework for fine-tuning a pre-trained language model like BERT to the task of moral foundation prediction. ME2-BERT integrates events and emotions for learning domain-invariant morality-relevant text representations. Our extensive experiments show that ME2-BERT outperforms existing state-of-the-art methods for moral foundation prediction, with an average increase up to 35% in the out-of-domain scenario.
BibTeX
@inproceedings{zangari-etal-2025-me2,
title = "{ME}2-{BERT}: Are Events and Emotions what you need for Moral Foundation Prediction?",
author = "Zangari, Lorenzo and
Greco, Candida M. and
Picca, Davide and
Tagarelli, Andrea",
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.638/",
pages = "9516--9532"
}