Elamur Research⌕
☰
home / papers / 2026 / The Moral Foundations Reddit Corpus

The Moral Foundations Reddit Corpus

Summary

Large, hand-labelled corpora are needed to detect moral sentiment automatically, because the task is highly subjective. The main existing resource, the Moral Foundations Twitter Corpus (MFTC), has two limits: it covers only Twitter, and it predates the revised Moral Foundations Theory, which divides Fairness into Equality and Proportionality. The authors address both gaps with the Moral Foundations Reddit Corpus (MFRC). It contains 16,123 English Reddit comments from 12 subreddits, and each comment was coded by at least three trained annotators using the updated MFT categories. Final labels come from a majority vote.

The release also includes demographic and psychological metadata about the annotators, so researchers can study how annotator background affects labels. As baselines, the authors fine-tuned BERT in single-label and multi-label setups. They compared it with Llama3-8B and Ministral-8B under zero-shot prompting, 5-shot prompting and LoRA-based PEFT. The fine-tuned encoders still outperform the LLMs. The authors conclude that human-annotated moral data remain essential, both for training classifiers and for evaluating AI alignment.

Key points

  • Corpus contents: MFRC has 16,123 comments from 12 subreddits, grouped into three buckets:
    • US politics: r/politics, r/conservative, r/antiwork, from 2020 to January 2021.
    • Everyday moral life: r/AmItheAsshole, r/relationshipadvice, r/confession, r/nostalgia.
    • French politics: comments matching keywords about the 2017 French presidential race.
  • Labels: there are 8 categories. Four are the foundations Purity, Authority, Loyalty and Care. Two come from splitting Fairness into Equality and Proportionality. The remaining two are Thin Morality and Implicit/Explicit Morality.
  • Baselines: BERT and ML-BERT, Llama and Ministral (zero-shot and 5-shot, single- and multi-label), and Llama with LoRA PEFT.
  • Main result: BERT-based models achieve the highest precision in most categories. For Purity, BERT reaches about 0.69, while the best LLM setting reaches about 0.32. PEFT narrows the gap but does not close it.
  • Stated limitations: the corpus is English-only Reddit data, it is framed strictly within revised MFT, and it does not test moral reasoning.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.63317/2b6xmbq3kphf

@inproceedings{trager2026moral,
  title = {{The Moral Foundations Reddit Corpus}},
  author = {Trager, Jackson P. and Ziabari, Alireza S. and Rahmati, Elnaz and Davani, Aida Mostafazadeh and Golazizian, Preni and Karimi-Malekabadi, Farzan and Omrani, Ali and Li, Zhihe and Kennedy, Brendan and Chochlakis, Georgios and Reimer, Nils Karl and Reyes, Melissa and Cheng, Kesley and Wei, Mellow and Merrifield, Christina and Khosravi, Arta and Alvarez, Evans and Dehghani, Morteza},
  booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference},
  year = {2026},
  doi = {10.63317/2b6xmbq3kphf},
  url = {https://doi.org/10.63317/2b6xmbq3kphf}
}

References

106 references, 6 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Suhaib Abdurahman, Mohammad Atari, Farzan Karimi-Malekabadi, Mona J Xue, Jackson Trager, Peter S Park, Preni Golazizian, Ali Omrani, and Morteza Dehghani. 2024. Perils and opportunities in using large language models in psychological research. PNAS nexus, 3(7):pgae245. find
  2. Suhaib Abdurahman, Nils K Reimer, Preni Golazizian, Elisa Baek, Yixuan Shen, Jackson Trager, Roshni Lulla, Jonas Kaplan, Carolyn Parkinson, and Morteza Dehghani. 2025. Targeting audiences’ moral values shapes misinformation sharing. Journal of Experimental Psychology: General. find
  3. Sandhini Agarwal, Lama Ahmad, Jason Ai, Sam Altman, Andy Applebaum, Edwin Arbus, Rahul K Arora, Yu Bai, Bowen Baker, Haiming Bao, et al. 2025. gpt-oss-120b & gpt-oss-20b model card. arXiv preprint arXiv:2508.10925. find our card
  4. Milad Alshomary, Roxanne El Baff, Timon Gurcke, and Henning Wachsmuth. 2022. The moral debater: A study on the computational generation of morally framed arguments. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 8782–8797. find
  5. Oscar Araque, Lorenzo Gatti, and Kyriaki Kalimeri. 2020. Moralstrength: Exploiting a moral lexicon and embedding similarity for moral foundations prediction. Knowledge-based systems, 191:105184. find
  6. Luigi Asprino, Luana Bulla, Stefano De Giorgis, Aldo Gangemi, Ludovica Marinucci, and Misael Mongiovì. 2022. Uncovering values: Detecting latent moral content from natural language with explainable and non-trained methods. In Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on… find
  7. Mohammad Atari, Aida Mostafazadeh Davani, Drew Kogon, Brendan Kennedy, Nripsuta Ani Saxena, Ian Anderson, and Morteza Dehghani. 2021. Morally homogeneous networks and radicalism. Social Psychological and Personality Science, page 19485506211059329. find
  8. Mohammad Atari and Morteza Dehghani. 2021. Language analysis in moral psychology. In Morteza Dehghani and Ryan L. Boyd, editors, Handbook of language analysis in psychology, pages 207–228. Guilford. find
  9. Mohammad Atari, Jonathan Haidt, Jesse Graham, Sena Koleva, Sean T Stevens, and Morteza Dehghani. 2023. Morality beyond the weird: How the nomological network of morality varies across cultures. Journal of Personality and Social Psychology, 125(5):1157. find
  10. Mohammad Atari, Matthias R. Mehl, Jesse Graham, John M. Doris, Norbert Schwarz, Aida Mostafazadeh Davani, Ali Omrani, Brendan Kennedy, Elaine Gonzalez, Nikki Jafarzadeh, Alyzeh Hussain, Arineh Mirinjian, Annabelle Madden, Rhea Bhatia, Alexander Burch, Allison Harlan, David A. Sbarra, Charles L. Rais… find
  11. Tolga Bolukbasi, Kai-Wei Chang, James Y Zou, Venkatesh Saligrama, and Adam T Kalai. 2016. Man is to computer programmer as woman is to homemaker? debiasing word embeddings. Advances in neural information processing systems, 29. find our card
  12. Arnout B Boot, Erik Tjong Kim Sang, Katinka Dijkstra, and Rolf A Zwaan. 2019. How character limit affects language usage in tweets. Palgrave Communications, 5(1):1–13. find
  13. William J Brady, Molly J Crockett, and Jay J Van Bavel. 2020. The mad model of moral contagion: The role of motivation, attention, and design in the spread of moralized content online. Perspectives on Psychological Science, 15(4):978–1010. find
  14. Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chri… find
  15. Luana Bulla, Stefano De Giorgis, Misael Mongiovì, and Aldo Gangemi. 2025. Large language models meet moral values: A comprehensive assessment of moral abilities. Computers in Human Behavior Reports, 17:100609. find
  16. Jason William Burton. 2022. Understanding and supporting belief accuracy in a digital world. Ph.D. thesis, Birkbeck, University of London. find
  17. Cristian Candia, Mohammad Atari, Nour Kteily, and Brian Uzzi. 2022. Overuse of moral language dampens content engagement on social media. Under review. find
  18. Eshwar Chandrasekharan, Mattia Samory, Shagun Jhaver, Hunter Charvat, Amy Bruckman, Cliff Lampe, Jacob Eisenstein, and Eric Gilbert. 2018. The internet’s hidden rules: An empirical study of reddit norm violations at micro, meso, and macro scales. Proceedings of the ACM on Human-Computer Interaction,… find
  19. Ziyu Chen, Junfei Sun, Chenxi Li, Tuan Dung Nguyen, Jing Yao, Xiaoyuan Yi, Xing Xie, Chenhao Tan, and Lexing Xie. 2025. Mova: Towards generalizable classification of human morals and values. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 33204–33248. find
  20. Calvin Yixiang Cheng and Scott A Hale. 2025. Beyond english: Evaluating automated measurement of moral foundations in non-english discourse with a chinese case study. arXiv preprint arXiv:2502.02451. — [arXiv:2502.02451](https://arxiv.org/abs/2502.02451) find
  21. Georgios Chochlakis, Alexandros Potamianos, Kristina Lerman, and Shrikanth Narayanan. 2025a. Aggregation artifacts in subjective tasks collapse large language models’ posteriors. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguis… find
  22. Georgios Chochlakis, Jackson Trager, Vedant Jhaveri, Nikhil Ravichandran, Alexandros Potamianos, and Shrikanth Narayanan. 2025b. Semantic f1 scores: Fair evaluation under fuzzy class boundaries. arXiv preprint arXiv:2509.21633. — [arXiv:2509.21633](https://arxiv.org/abs/2509.21633) find
  23. Stephan A Curiskis, Barry Drake, Thomas R Osborn, and Paul J Kennedy. 2020. An evaluation of document clustering and topic modelling in two online social networks: Twitter and reddit. Information Processing & Management, 57(2):102034. find
  24. Srayan Datta and Eytan Adar. 2019. Extracting inter-community conflicts in reddit. In Proceedings of the international AAAI conference on Web and Social Media, volume 13, pages 146–157. find
  25. Aida Mostafazadeh Davani, Mohammad Atari, Brendan Kennedy, and Morteza Dehghani. 2023. Hate speech classifiers learn normative social stereotypes. Transactions of the Association for Computational Linguistics, 11:300–319. find
  26. Aida Mostafazadeh Davani, Mark Díaz, and Vinodkumar Prabhakaran. 2022. Dealing with disagreements: Looking beyond the majority vote in subjective annotations. Transactions of the Association for Computational Linguistics, 10:92–110. find our card
  27. Munmun De Choudhury and Sushovan De. 2014. Mental health discourse on reddit: Self-disclosure, social support, and anonymity. In Eighth international AAAI conference on weblogs and social media. find
  28. Morteza Dehghani, Kate Johnson, Joe Hoover, Eyal Sagi, Justin Garten, Niki Jitendra Parmar, Stephen Vaisey, Rumen Iliev, and Jesse Graham. 2016. Purity homophily in social networks. Journal of Experimental Psychology: General, 145(3):366. find
  29. Peter DeScioli and Robert Kurzban. 2013. A solution to the mysteries of morality. Psychological bulletin, 139(2):477. find
  30. Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. Bert: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 conference of the North American chapter of the association for computational linguistics: human language technologies,… find
  31. Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al. 2024. The llama 3 herd of models. arXiv e-prints, pages arXiv– 2407. find
  32. Naomi Ellemers, Jojanneke Van Der Toorn, Yavor Paunov, and Thed Van Leeuwen. 2019. The psychology of morality: A review and analysis of empirical studies published from 1940 through 2017. Personality and Social Psychology Review, 23(4):332–366. find
  33. Benjamin Enke. 2019. Kinship, cooperation, and the evolution of moral systems. The Quarterly Journal of Economics, 134(2):953–1019. find
  34. Casey Fiesler. 2019. Ethical considerations for research involving (speculative) public data. Proceedings of the ACM on Human-Computer Interaction, 3(GROUP):1–13. find
  35. Joseph L Fleiss. 1971. Measuring nominal scale agreement among many raters. Psychological bulletin, 76(5):378. find
  36. JA Frimer, R Boghrati, J Haidt, J Graham, and M Dehghani. 2019. Moral foundations dictionary 2.0. find
  37. Akinori Fujino, Hideki Isozaki, and Jun Suzuki. 2008. Multi-label text categorization with model combination based on f1-score maximization. In Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-II. find
  38. Justin Garten, Joe Hoover, Kate M Johnson, Reihane Boghrati, Carol Iskiwitch, and Morteza Dehghani. 2018. Dictionaries and distributions: Combining expert knowledge and large scale textual data content analysis. Behavior research methods, 50(1):344–361. find
  39. Justin Garten, Brendan Kennedy, Joe Hoover, Kenji Sagae, and Morteza Dehghani. 2019a. Incorporating demographic embeddings into language understanding. Cognitive science, 43(1):e12701. find
  40. Justin Garten, Brendan Kennedy, Kenji Sagae, and Morteza Dehghani. 2019b. Measuring the importance of context when modeling language comprehension. Behavior research methods, 51(2):480–492. find
  41. Tiana Gaudette, Ryan Scrivens, Garth Davies, and Richard Frank. 2021. Upvoting extremism: Collective identity formation and the extreme right on reddit. New Media & Society, 23(12):3491–3508. find
  42. Jesse Graham, Jonathan Haidt, Sena Koleva, Matt Motyl, Ravi Iyer, Sean P Wojcik, and Peter H Ditto. 2013. Moral foundations theory: The pragmatic validity of moral pluralism. In Advances in experimental social psychology, volume 47, pages 55–130. Elsevier. find
  43. Jesse Graham, Jonathan Haidt, and Brian A Nosek. 2009. Liberals and conservatives rely on different sets of moral foundations. Journal of personality and social psychology, 96(5):1029. find
  44. Jesse Graham, Brian A Nosek, Jonathan Haidt, Ravi Iyer, Spassena Koleva, and Peter H Ditto. 2011. Mapping the moral domain. Journal of personality and social psychology, 101(2):366. find
  45. Joshua D Greene. 2014. Beyond point-and-shoot morality: Why cognitive (neuro) science matters for ethics. Ethics, 124(4):695–726. find
  46. Siyi Guo, Negar Mokhberian, and Kristina Lerman. 2023. A data fusion framework for multi-domain morality learning. In Proceedings of the international AAAI conference on web and social media, volume 17, pages 281–291. find
  47. Jonathan Haidt. 2012. The righteous mind: Why good people are divided by politics and religion. Vintage. find
  48. Jonathan Haidt and Craig Joseph. 2004. Intuitive ethics: How innately prepared intuitions generate culturally variable virtues. Daedalus, 133(4):55– 66. find
  49. Brenna Helm, Ryan Scrivens, Thomas J Holt, Steve Chermak, and Richard Frank. 2022. Examining incel subculture on reddit. Journal of Crime and Justice, pages 1–19. find
  50. Joe Hoover, Gwenyth Portillo-Wightman, Leigh Yeh, Shreya Havaldar, Aida Mostafazadeh Davani, Ying Lin, Brendan Kennedy, Mohammad Atari, Zahra Kamel, Madelyn Mendlen, et al. 2020. Moral foundations twitter corpus: A collection of 35k tweets annotated for moral sentiment. Social Psychological and Pers… find
  51. Frederic R Hopp, Jacob T Fisher, Devin Cornell, Richard Huskey, and René Weber. 2021. The extended moral foundations dictionary (emfd): Development and applications of a crowd-sourced approach to extracting moral intuitions from text. Behavior Research Methods, 53(1):232–246. find
  52. Dirk Hovy and Shrimai Prabhumoye. 2021. Five sources of bias in natural language processing. Language and Linguistics Compass, 15(8):e12432. find
  53. Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022. Lora: Low-rank adaptation of large language models. In ICLR. Open-Review.net. find
  54. Albert Jiang, Alexandre Abou Chahine, Alexandre Sablayrolles, Alexis Tacnet, Alodie Boissonnet, Alok Kothari, Amélie Héliou, Andy Lo, Anna Peronnin, Antoine Meunier, Antoine Roux, Antonin Faure, Aritra Paul, Arthur Darcet, Arthur Mensch, Audrey Herblin-Stoop, Augustin Garreau, Austin Birky, Avinash… find
  55. Farzan Karimi-Malekabadi, Suhaib Abdurahman, Zhivar Sourati, Jackson Trager, and Morteza Dehghani. 2026. Theory trace card: Theory-driven socio-cognitive evaluation of llms. arXiv preprint arXiv:2601.01878. — [arXiv:2601.01878](https://arxiv.org/abs/2601.01878) find
  56. Ian Keen. 2015. The language of morality. The Australian Journal of Anthropology, 26(3):332– 348. find
  57. Brendan Kennedy, Ashwini Ashokkumar, Ryan L Boyd, and Morteza Dehghani. 2022a. Text analysis for psychology: Methods, principles, and practices. Handbook of Language Analysis in Psychology. find
  58. Brendan Kennedy, Mohammad Atari, Aida Mostafazadeh Davani, Joe Hoover, Ali Omrani, Jesse Graham, and Morteza Dehghani. 2021. Moral concerns are differentially observable in language. Cognition, 212:104696. find
  59. Brendan Kennedy, Mohammad Atari, Aida Mostafazadeh Davani, Leigh Yeh, Ali Omrani, Yehsong Kim, Kris Coombs, Shreya Havaldar, Gwenyth Portillo-Wightman, Elaine Gonzalez, et al. 2022b. Introducing the gab hate corpus: defining and applying hate-based rhetoric to social media posts at scale. Language R… find
  60. Brendan Kennedy, Preni Golazizian, Jackson Trager, Mohammad Atari, Joe Hoover, Aida Mostafazadeh Davani, and Morteza Dehghani. 2023. The (moral) language of hate. PNAS nexus, 2(7):pgad210. find
  61. Blair Kidwell, Adam Farmer, and David M Hardesty. 2013. Getting liberals and conservatives to go green: Political ideology and congruent appeals. Journal of Consumer Research, 40(2):350–367. find
  62. Srijan Kumar, William L Hamilton, Jure Leskovec, and Dan Jurafsky. 2018. Community interaction and conflict on the web. In Proceedings of the 2018 world wide web conference, pages 933– 943. find
  63. Alex Gwo Jen Lan and Ivandré Paraboni. 2022. Text-and author-dependent moral foundations classification. New Review of Hypermedia and Multimedia, pages 1–21. find
  64. Yuanyuan Lei, Md Messal Monem Miah, Ayesha Qamar, Sai Ramana Reddy, Jonathan Tong, Haotian Xu, and Ruihong Huang. 2024. Emona: Event-level moral opinions in news articles. arXiv preprint arXiv:2404.01715. find
  65. Leon Li and Michael Tomasello. 2021. On the moral functions of language. Social Cognition, 39(1):99–116. find
  66. Eneldo Loza Mencía, Moritz Kulessa, Simon Bohlender, and Johannes Fürnkranz. 2023. Tree-based dynamic classifier chains. Machine Learning, 112(11):4129–4165. find
  67. Morgan Marietta. 2008. From my cold, dead hands: Democratic consequences of sacred rhetoric. The Journal of Politics, 70(3):767–779. find
  68. Salma Moaz. 2020. Using Moral Foundations Framing to Influence Partisan Attitudes Toward Latino Immigrants. Ph.D. thesis, Loyola University Chicago. find
  69. Negar Mokhberian, Frederic R Hopp, Bahareh Harandizadeh, Fred Morstatter, and Kristina Lerman. 2022. Noise audits improve moral foundation classification. In 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pages 147–154. IEEE. find
  70. Dena F Mujtaba and Nihar R Mahapatra. 2019. Ethical considerations in ai-based recruitment. In 2019 IEEE International Symposium on Technology and Society (ISTAS), pages 1–7. IEEE. find
  71. Ece Çiğdem Mutlu, Toktam Oghaz, Ege Tütüncüler, Jasser Jasser, and Ivan Garibay. 2020. Quantifying latent moral foundations in twitter narratives: The case of the syrian white helmets misinformation. arXiv preprint arXiv:2004.13142. — [arXiv:2004.13142](https://arxiv.org/abs/2004.13142) find
  72. Tuan Dung Nguyen, Ziyu Chen, Nicholas George Carroll, Alasdair Tran, Colin Klein, and Lexing Xie. 2024. Measuring moral dimensions in social media with mformer. In Proceedings of the international AAAI conference on web and social media, volume 18, pages 1134–1147. find
  73. Vinodkumar Prabhakaran, Aida Mostafazadeh Davani, and Mark Diaz. 2021. On releasing annotator-level labels and information in datasets. arXiv preprint arXiv:2110.05699. find our card
  74. Vjosa Preniqi, Iacopo Ghinassi, Julia Ive, Kyriaki Kalimeri, and Charalampos Saitis. 2024. Automatic detection of moral values in music lyrics. arXiv preprint arXiv:2407.18787. — [arXiv:2407.18787](https://arxiv.org/abs/2407.18787) find
  75. Nicholas Proferes, Naiyan Jones, Sarah Gilbert, Casey Fiesler, and Michael Zimmer. 2021. Studying reddit: A systematic overview of disciplines, approaches, methods, and ethics. Social Media+ Society, 7(2):20563051211019004. find
  76. Benjamin Grant Purzycki, Anne C Pisor, Coren Apicella, Quentin Atkinson, Emma Cohen, Joseph Henrich, Richard McElreath, Rita A McNamara, Ara Norenzayan, Aiyana K Willard, et al. 2018. The cognitive and cultural foundations of moral behavior. Evolution and Human Behavior, 39(5):490–501. find
  77. Muhammad Reza Qorib, Geonsik Moon, and Hwee Tou Ng. 2024. Are decoder-only language models better than encoder-only language models in understanding word meaning? In Findings of the Association for Computational Linguistics: ACL 2024, pages 16339–16347, Bangkok, Thailand. Association for Computation… find
  78. Aida Ramezani and Yang Xu. 2024. Moral association graph: A cognitive model for moral inference. In Proceedings of the Annual Meeting of the Cognitive Science Society, volume 46. find
  79. Steve Rathje, Dan-Mircea Mirea, Ilia Sucholutsky, Raja Marjieh, Claire E Robertson, and Jay J Van Bavel. 2024. Gpt is an effective tool for multilingual psychological text analysis. Proceedings of the National Academy of Sciences, 121(34):e2308950121. find
  80. Gabriel Roccabruna, Massimo Rizzoli, and Giuseppe Riccardi. 2024. Will LLMs replace the encoder-only models in temporal relation classification? In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 20402–20415, Miami, Florida, USA. Association for Computat… find
  81. Kevin Roose. 2021. The gamestop reckoning was a long time coming. Posted 28-January-2021, The New York Times, www.nytimes.com/2021/01/28/technology/gamestop-stock.html. find
  82. Alexander Ruch, Ari Decter-Frain, and Raghav Batra. 2022. Millions of co-purchases and reviews reveal the spread of polarization and lifestyle politics across online markets. arXiv preprint arXiv:2201.06556. — [arXiv:2201.06556](https://arxiv.org/abs/2201.06556) find
  83. Eyal Sagi and Morteza Dehghani. 2014. Measuring moral rhetoric in text. Social science computer review, 32(2):132–144. find
  84. Julius Sim and Chris C Wright. 2005. The kappa statistic in reliability studies: use, interpretation, and sample size requirements. Physical therapy, 85(3):257–268. find
  85. Johanna Simfors and Rasmus Rudling. 2020. How does the degree of anonymity affect our morals?: A study examining behavioural changes in online communication. find
  86. Maciej Skorski and Alina Landowska. 2025. Beyond human judgment: A bayesian evaluation of llms’ moral values understanding. In Proceedings of the 2nd Workshop on Uncertainty-Aware NLP (UncertaiNLP 2025), pages 17–26. find
  87. Ahmed Soliman, Jan Hafer, and Florian Lemmerich. 2019. A characterization of political communities on reddit. In Proceedings of the 30th ACM conference on hypertext and Social Media, pages 259–263. find
  88. Kate Starbird, Jim Maddock, Mania Orand, Peg Achterman, and Robert M Mason. 2014. Rumors, false flags, and digital vigilantes: Misinformation on twitter after the 2013 boston marathon bombing. find
  89. IConference 2014 proceedings. find
  90. Jackson Trager and Mohammad Atari. 2025. The immorality of too much money. PNAS nexus, 4(6):pgaf158. find
  91. Jackson Trager, Francielle Vargas, Diego Alves, Matteo Guida, Mikel K Ngueajio, Ameeta Agrawal, Flor Plaza-del Arco, Yalda Daryanai, and Farzan Karimi-Malekabadi. 2025. Mftcxplain: A multilingual benchmark dataset for evaluating the moral reasoning of llms through hate speech multi-hop explanation.… — [arXiv:2506.19073](https://arxiv.org/abs/2506.19073) find
  92. Anthony Henry Triggs, Kristian Møller, and Christina Neumayer. 2021. Context collapse and anonymity among queer reddit users. new media & society, 23(1):5–21. find
  93. Grigorios Tsoumakas and Ioannis Katakis. 2007. Multi-label classification: An overview. International Journal of Data Warehousing and Mining (IJDWM), 3(3):1–13. find
  94. Reddit’s 2020 year in review. Posted 8-December-2020, Upvoted: The Official Reddit Blog, www.redditinc.com/blog/reddits-2020-year-in-review/. find
  95. Michiel Van Der Meer, Piek Vossen, Catholijn M Jonker, and Pradeep K Murukannaiah. 2023. Do differences in values influence disagreements in online discussions? arXiv preprint arXiv:2310.15757. find
  96. Pekka Väyrynen. 2016. Thick ethical concepts. The Stanford Encyclopedia of Philosophy (Spring 2021 Edition). find
  97. Jan G Voelkel, Mashail Malik, Chrystal Redekopp, and Robb Willer. 2022. Changing americans’ attitudes about immigration: Using moral framing to bolster factual arguments. The ANNALS of the American Academy of Political and Social Science, 700(1):73–85. find
  98. Rong Wang and Wenlin Liu. 2021. Different pathways to identify moral framing from media content: A response to hopp and weber. Communication Monographs, 88(3):380–388. find
  99. Christopher Wolsko. 2017. Expanding the range of environmental values: Political orientation, moral foundations, and the common ingroup. Journal of Environmental Psychology, 51:284–294. find
  100. Yuexin Wu and Xiaolei Huang. 2022. Unsupervised reinforcement adaptation for class-imbalanced text classification. In Proceedings of the 11th Joint Conference on Lexical and Computational Semantics, pages 311–322, Seattle, Washington. Association for Computational Linguistics. find
  101. Hiroaki Yamane, Yusuke Mori, and Tatsuya Harada. 2021. Humor meets morality: Joke generation based on moral judgement. Information Processing & Management, 58(3):102520. find
  102. An Yang, Anfeng Li, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chang Gao, Chengen Huang, Chenxu Lv, et al. 2025. Qwen3 technical report. arXiv preprint arXiv:2505.09388. find our card
  103. Lorenzo Zangari, Candida M Greco, Davide Picca, and Andrea Tagarelli. 2025a. Me2-bert: Are events and emotions what you need for moral foundation prediction? In Proceedings of the 31st International Conference on Computational Linguistics, pages 9516–9532. find
  104. Lorenzo Zangari, Candida Maria Greco, Davide Picca, and Andrea Tagarelli. 2025b. A survey on moral foundation theory and pre-trained language models: Current advances and challenges. AI & SOCIETY, pages 1–26. find
  105. Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2017. Men also like shopping: Reducing gender bias amplification using corpus-level constraints. arXiv preprint arXiv:1707.09457. find our card
  106. Appendix: Appendix includes the moral foundations coding guide, additional model results, prompts, and Theory Trace Card (Karimi-Malekabadi et al., 2026). For additional material, see the huggingface 3 . find

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/trager-2026-moral-foundations-reddit-corpus/