@inproceedings{trager-etal-2026-moral,
title = "The Moral Foundations {R}eddit Corpus",
author = "Trager, Jackson P. and
S. Ziabari, Alireza and
Rahmati, Elnaz and
Mostafazadeh Davani, Aida and
Golazizian, Preni and
Karimi-Malekabadi, Farzan and
Omrani, Ali and
Li, Zhihe and
Kennedy, Brendan and
Chochlakis, Georgios and
Karl Reimer, Nils and
Reyes, Melissa and
Cheng, Kesley and
Wei, Mellow and
Merrifield, Christina and
Khosravi, Arta and
Alvarez, Evans and
Dehghani, Morteza",
editor = "Piperidis, Stelios and
Bel, N{\'u}ria and
van den Heuvel, Henk and
Ide, Nancy and
Krek, Simon and
Toral, Antonio",
booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
month = may,
year = "2026",
address = "Palma de Mallorca, Spain",
publisher = "ELRA Language Resource Association",
url = "https://aclanthology.org/2026.lrec-1.507/",
doi = "10.63317/2b6xmbq3kphf",
pages = "6383--6407",
abstract = "Moral framing and sentiment can affect a variety of online and offline behaviors, including donation, environmental action, political engagement, and protest. Various computational methods in Natural Language Processing (NLP) have been used to detect moral sentiment from textual data, but achieving strong performance in such subjective tasks requires large, hand-annotated datasets. Previous corpora annotated for moral sentiment have proven valuable and have generated new insights both within NLP and across the social sciences, but have been limited to Twitter. To facilitate improving our understanding of the role of moral rhetoric, we present the Moral Foundations Reddit Corpus, a collection of 16,123 English Reddit comments that have been curated from 12 distinct subreddits, hand-annotated by at least three trained annotators for 8 categories of moral sentiment (i.e., Care, Proportionality, Equality, Purity, Authority, Loyalty, Thin Morality, Implicit/Explicit Morality) based on the updated Moral Foundations Theory (MFT) framework. We evaluate baselines using large language models (Llama3-8B, Ministral-8B) in zero-shot, few-shot, and PEFT (Parameter-Efficient Fine-Tuning) settings, comparing their performance to fine-tuned encoder-only models like BERT (Bidirectional Encoder Representations from Transformers). The results show that LLMs continue to lag behind fine-tuned encoders on this subjective task, underscoring the ongoing need for human-annotated moral corpora for AI alignment evaluation"
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<abstract>Moral framing and sentiment can affect a variety of online and offline behaviors, including donation, environmental action, political engagement, and protest. Various computational methods in Natural Language Processing (NLP) have been used to detect moral sentiment from textual data, but achieving strong performance in such subjective tasks requires large, hand-annotated datasets. Previous corpora annotated for moral sentiment have proven valuable and have generated new insights both within NLP and across the social sciences, but have been limited to Twitter. To facilitate improving our understanding of the role of moral rhetoric, we present the Moral Foundations Reddit Corpus, a collection of 16,123 English Reddit comments that have been curated from 12 distinct subreddits, hand-annotated by at least three trained annotators for 8 categories of moral sentiment (i.e., Care, Proportionality, Equality, Purity, Authority, Loyalty, Thin Morality, Implicit/Explicit Morality) based on the updated Moral Foundations Theory (MFT) framework. We evaluate baselines using large language models (Llama3-8B, Ministral-8B) in zero-shot, few-shot, and PEFT (Parameter-Efficient Fine-Tuning) settings, comparing their performance to fine-tuned encoder-only models like BERT (Bidirectional Encoder Representations from Transformers). The results show that LLMs continue to lag behind fine-tuned encoders on this subjective task, underscoring the ongoing need for human-annotated moral corpora for AI alignment evaluation</abstract>
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%0 Conference Proceedings
%T The Moral Foundations Reddit Corpus
%A Trager, Jackson P.
%A S. Ziabari, Alireza
%A Rahmati, Elnaz
%A Mostafazadeh Davani, Aida
%A Golazizian, Preni
%A Karimi-Malekabadi, Farzan
%A Omrani, Ali
%A Li, Zhihe
%A Kennedy, Brendan
%A Chochlakis, Georgios
%A Karl Reimer, Nils
%A Reyes, Melissa
%A Cheng, Kesley
%A Wei, Mellow
%A Merrifield, Christina
%A Khosravi, Arta
%A Alvarez, Evans
%A Dehghani, Morteza
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F trager-etal-2026-moral
%X Moral framing and sentiment can affect a variety of online and offline behaviors, including donation, environmental action, political engagement, and protest. Various computational methods in Natural Language Processing (NLP) have been used to detect moral sentiment from textual data, but achieving strong performance in such subjective tasks requires large, hand-annotated datasets. Previous corpora annotated for moral sentiment have proven valuable and have generated new insights both within NLP and across the social sciences, but have been limited to Twitter. To facilitate improving our understanding of the role of moral rhetoric, we present the Moral Foundations Reddit Corpus, a collection of 16,123 English Reddit comments that have been curated from 12 distinct subreddits, hand-annotated by at least three trained annotators for 8 categories of moral sentiment (i.e., Care, Proportionality, Equality, Purity, Authority, Loyalty, Thin Morality, Implicit/Explicit Morality) based on the updated Moral Foundations Theory (MFT) framework. We evaluate baselines using large language models (Llama3-8B, Ministral-8B) in zero-shot, few-shot, and PEFT (Parameter-Efficient Fine-Tuning) settings, comparing their performance to fine-tuned encoder-only models like BERT (Bidirectional Encoder Representations from Transformers). The results show that LLMs continue to lag behind fine-tuned encoders on this subjective task, underscoring the ongoing need for human-annotated moral corpora for AI alignment evaluation
%R 10.63317/2b6xmbq3kphf
%U https://aclanthology.org/2026.lrec-1.507/
%U https://doi.org/10.63317/2b6xmbq3kphf
%P 6383-6407
Markdown (Informal)
[The Moral Foundations Reddit Corpus](https://aclanthology.org/2026.lrec-1.507/) (Trager et al., LREC 2026)
ACL
- Jackson P. Trager, Alireza S. Ziabari, Elnaz Rahmati, Aida Mostafazadeh Davani, Preni Golazizian, Farzan Karimi-Malekabadi, Ali Omrani, Zhihe Li, Brendan Kennedy, Georgios Chochlakis, Nils Karl Reimer, Melissa Reyes, Kesley Cheng, Mellow Wei, Christina Merrifield, Arta Khosravi, Evans Alvarez, and Morteza Dehghani. 2026. The Moral Foundations Reddit Corpus. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 6383–6407, Palma de Mallorca, Spain. ELRA Language Resource Association.