The DOI matches its Crossref record; 48 of the 50 references it cites were found in a registry or an index.
Moral Foundations Twitter Corpus: A Collection of 35k Tweets Annotated for Moral Sentiment
Open accessAbstract
Research has shown that accounting for moral sentiment in natural language can yield insight into a variety of on- and off-line phenomena such as message diffusion, protest dynamics, and social distancing. However, measuring moral sentiment in natural language is challenging, and the difficulty of this task is exacerbated by the limited availability of annotated data. To address this issue, we introduce the Moral Foundations Twitter Corpus, a collection of 35,108 tweets that have been curated from seven distinct domains of discourse and hand annotated by at least three trained annotators for 10 categories of moral sentiment. To facilitate investigations of annotator response dynamics, we also provide psychological and demographic metadata for each annotator. Finally, we report moral sentiment classification baselines for this corpus using a range of popular methodologies.
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“Further comparisons (Tables S7 and S8 in Rathje et al. (75)) on another moral foundations dataset, on which the BERT model was not fine-tuned (MFTC; (81)), showed that BERT, despite being applied cross-context, outperformed GPT-4 on the Authority and Purity foundations, and GPT-4-Turbo also on the Loyalty foundation.”
From Perils and opportunities in using large language models in psychological research (2024) · cites this paper as [81]
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Perils and opportunities in using large language models in psychological research
Abdurahman, S., Atari, M., Karimi-Malekabadi, F., Xue, M. J., Trager, J., Park, P. S., Golazizian, P., Omrani, A., & Dehghani, M. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae245 · Cited by 111
“Further comparisons (Tables S7 and S8in Rathje et al. (75)) on another moral foundations dataset, on which the BERT model was not fine-tuned (MFTC; (81)), showed that BERT, despite being applied cross-context, outperformed GPT-4 on the Authority and Purity foundations, and GPT-4-Turbo also on the…”
Self-citationMacanovic, A. (2022) · Social Science Research · doi:10.1016/j.ssresearch.2022.102784 · Cited by 120
Language-based game theory in the age of artificial intelligence
Capraro, V., Paolo, R. D., Perc, M., & Pizziol, V. (2024) · Journal of The Royal Society Interface · doi:10.1098/rsif.2023.0720 · Cited by 97
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Self-citationAgainst Empathy Bias: The Moral Value of Equitable Empathy
Fowler, Z., Law, K. F., & Gaesser, B. (2021) · Psychological Science · doi:10.1177/0956797620979965 · Cited by 95
Metadata
- Authors
- Hoover, J., Portillo-Wightman, G., Yeh, L., Havaldar, S., Davani, A. M., Lin, Y., Kennedy, B., Atari, M., Kamel, Z., Mendlen, M., Moreno, G., Park, C., Chang, T. E., Chin, J., Leong, C., Leung, J. Y., Mirinjian, A., & Dehghani, M.
- Affiliations
- University of Southern California (US)
- Rensselaer Polytechnic Institute (US)
- Corresponding author
- Dehghani, Morteza
- ORCID
- Venue
- Social Psychological and Personality Science
- Publisher
- SAGE Publications
- Published
- 2020-02-19
- Volume
- 11
- Issue
- 8
- Pages
- 1057-1071
- ISSN
- 1948-5506 (ISSN-L)
- 1948-5514
- OpenAlex
- W3008655042
- Semantic Scholar
- a95ee39bda53cf7cbf1677d1bbac9d2be34fcc5a
- Cited by
- 177
- References
- 50
- Citations by year
- 2026: 10 · 2025: 19 · 2024: 36 · 2023: 41 · 2022: 39 · 2021: 24 · 2020: 7
- FWCI
- 10.91
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Social Psychological and Personality Science (publishedVersion)
- PsyArXiv (OSF Preprints) (submittedVersion)
- PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
- Funders
- Army Research Laboratory
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
- Life Sciences › Neuroscience › Cognitive Neuroscience › Psychology of Moral and Emotional Judgment
- Keywords
- moral sentiments, moral foundations, Twitter, annotated corpus, social media discourse, message dissemination, protest dynamics, social distancing
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