The Moralization Corpus: Frame-Based Annotation and Analysis of Moralizing Speech Acts across Diverse Text Genres
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Abstract (arXiv)
Moralizations - arguments that invoke moral values to justify demands or positions - are a yet underexplored form of persuasive communication. We present the Moralization Corpus, a novel multi-genre dataset designed to analyze how moral values are strategically used in argumentative discourse. Moralizations are pragmatically complex and often implicit, posing significant challenges for both human annotators and NLP systems. We develop a frame-based annotation scheme that captures the constitutive elements of moralizations - moral values, demands, and discourse protagonists - and apply it to a diverse set of German texts, including political debates, news articles, and online discussions. The corpus enables fine-grained analysis of moralizing language across communicative formats and domains. We further evaluate several large language models (LLMs) under varied prompting conditions for the task of moralization detection and moralization component extraction and compare it to human annotations in order to investigate the challenges of automatic and manual analysis of moralizations. Results show that detailed prompt instructions has a greater effect than few-shot or explanation-based prompting, and that moralization remains a highly subjective and context-sensitive task. We release all data, annotation guidelines, and code to foster future interdisciplinary research on moral discourse and moral reasoning in NLP.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 11 of its 44 references that are in the map. First posted on arXiv 17 Dec 2025.
Builds on
11 of 44 references.
References · 11
- 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
- 2020Aligning AI With Shared Human Valuescited by 723
- 2021Large Pre-trained Language Models Contain Human-like Biases of What is Right and Wrong to Docited by 178
- 2024VariErr NLI: Separating Annotation Error from Human Label Variationcited by 42
- 2022Speaking Multiple Languages Affects the Moral Bias of Language Modelscited by 34
- 2021Identifying Morality Frames in Political Tweets using Relational Learningcited by 26
- 2022Understanding COVID-19 Vaccine Campaign on Facebook using Minimal Supervisioncited by 9
- 2024Larger Language Models Don't Care How You Think: Why Chain-of-Thought Prompting Fails in Subjective Taskscited by 8
- 2023Towards Few-Shot Identification of Morality Frames using In-Context Learningcited by 7
- 2023MOKA: Moral Knowledge Augmentation for Moral Event Extractioncited by 7
- 2024EMONA: Event-level Moral Opinions in News Articlescited by 5
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Citing papers per year: 2026: 2.
2 papers.