Analysis of Moral Judgment on Reddit
Abstract
Moral outrage has become synonymous with social media in recent years. However, the preponderance of academic analysis on social media websites has focused on hate speech and misinformation. This article focuses on analyzing moral judgments rendered on social media by capturing the moral judgments that are passed in the subreddit /r/AmITheAsshole on Reddit. Using the labels associated with each judgment, we train a classifier that can take a comment and determine whether it judges the user who made the original post to have positive or negative moral valence. Then, we employ human annotators to verify the performance of this classifier and use it to investigate an assortment of website traits surrounding moral judgments in ten other subreddits. Our analysis looks to answer three questions related to moral judgments and how these apply to different aspects of Reddit. We seek to determine whether moral valence impacts post scores, in which subreddit communities contain users with more negative moral valence, and whether gender and age play a role in moral judgments. Findings from our experiments show that users upvote posts more often when posts contain positive moral valence. We also find that certain subreddits, such as /r/confessions, attract users who tend to be judged more negatively. Finally, we found that men and older age were judged negatively more often.
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The sentiment of comments can be predicted with 0.89 accuracy.
“(although the sentiment of comments can be predicted with 0.89 accuracy Botzer et al. (2022))”
From Sycophantic AI decreases prosocial intentions and promotes dependence (2026) · cites this paper as Botzer et al. (2022)
Cites
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · doi:10.18653/v1/n19-1423 · Cited by 48,293 · see citing works
VADER: a parsimonious rule-based model for sentiment analysis of social media text
Hutto, C., & Gilbert, E. (2014) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v8i1.14550 · Cited by 6,087 · see citing works
Moral outrage in the digital age
Crockett, M. J. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0213-3 · Cited by 618 · cited 2× · see citing works
“: Recent research into morality has found that immoral acts posted online trigger stronger moral outrage responses than if the act was witnessed in person [17], [18].”
BackgroundPANDORA Talks: Personality and Demographics on Reddit
Gjurković, M., Karan, M., Vukojević, I., Bošnjak, M., & Snajder, J. (2021) · Proceedings of the Ninth International Workshop on Natural Language Processing for Social Media · doi:10.18653/v1/2021.socialnlp-1.12 · Cited by 58 · see citing works
Sawaoka, T., & Monin, B. (2018) · Psychological Science · doi:10.1177/0956797618780658 · Cited by 54 · see citing works
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Sycophantic AI decreases prosocial intentions and promotes dependence
Cheng, M., Lee, C., Khadpe, P., Yu, S., Han, D., & Jurafsky, D. (2026) · Science · doi:10.1126/science.aec8352 · Cited by 185 · see citing works
- Authors
- Botzer, N., Gu, S., & Weninger, T.
- Affiliations
- University of Notre Dame (US)
- Venue
- IEEE Transactions on Computational Social Systems
- Published
- 2023-06
- Volume
- 10
- Issue
- 3
- Pages
- 947-957
- ISSN
- 2329-924X (ISSN-L)
- 2373-7476
- OpenAlex
- W4226339449
- Cited by
- 34
- References
- 5
- Citations by year
- 2026: 1 · 2025: 8 · 2024: 14 · 2023: 11
- FWCI
- 2.71
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Computational Social Systems (publishedVersion)
- Funders
- U.S. Army Research Office (W911NF-17-1-0448)
- U.S. Defense Advanced Research Projects Agency (DARPA W911NF-17-C-0094)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
- Life Sciences › Neuroscience › Cognitive Neuroscience › Psychology of Moral and Emotional Judgment
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Keywords
- moral judgment, moral outrage, Reddit, moral valence, subreddits, gender differences, age differences, online communities
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