MOKA: Moral Knowledge Augmentation for Moral Event Extraction

Xinliang Frederick Zhang, Winston Wu, Nicholas Beauchamp, Lu Wang

Abstract
News media often strive to minimize explicit moral language in news articles, yet most articles are dense with moral values as expressed through the reported events themselves. However, values that are reflected in the intricate dynamics among *participating entities* and *moral events* are far more challenging for most NLP systems to detect, including LLMs. To study this phenomenon, we annotate a new dataset, **MORAL EVENTS**, consisting of 5,494 structured event annotations on 474 news articles by diverse US media across the political spectrum. We further propose **MOKA**, a moral event extraction framework with **MO**ral **K**nowledge **A**ugmentation, which leverages knowledge derived from moral words and moral scenarios to produce structural representations of morality-bearing events. Experiments show that **MOKA** outperforms competitive baselines across three moral event understanding tasks. Further analysis shows even ostensibly nonpartisan media engage in the selective reporting of moral events.
Anthology ID:
2024.naacl-long.252
Volume:
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Kevin Duh, Helena Gomez, Steven Bethard
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4481–4502
Language:
URL:
https://aclanthology.org/2024.naacl-long.252
DOI:
10.18653/v1/2024.naacl-long.252
Bibkey:
Cite (ACL):
Xinliang Frederick Zhang, Winston Wu, Nicholas Beauchamp, and Lu Wang. 2024. MOKA: Moral Knowledge Augmentation for Moral Event Extraction. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 4481–4502, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
MOKA: Moral Knowledge Augmentation for Moral Event Extraction (Zhang et al., NAACL 2024)
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PDF:
https://preview.aclanthology.org/dois-2013-emnlp/2024.naacl-long.252.pdf
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