mlsanityData to 7 Oct 2026

Social Chemistry 101: Learning to Reason about Social and Moral Norms

arXiv 2011.00620 ↗First posted 1 Nov 2020cs.CL cs.AIcited by 253

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Cited by 28 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Social norms -- the unspoken commonsense rules about acceptable social behavior -- are crucial in understanding the underlying causes and intents of people's actions in narratives. For example, underlying an action such as "wanting to call cops on my neighbors" are social norms that inform our conduct, such as "It is expected that you report crimes." We present Social Chemistry, a new conceptual formalism to study people's everyday social norms and moral judgments over a rich spectrum of real life situations described in natural language. We introduce Social-Chem-101, a large-scale corpus that catalogs 292k rules-of-thumb such as "it is rude to run a blender at 5am" as the basic conceptual units. Each rule-of-thumb is further broken down with 12 different dimensions of people's judgments, including social judgments of good and bad, moral foundations, expected cultural pressure, and assumed legality, which together amount to over 4.5 million annotations of categorical labels and free-text descriptions. Comprehensive empirical results based on state-of-the-art neural models demonstrate that computational modeling of social norms is a promising research direction. Our model framework, Neural Norm Transformer, learns and generalizes Social-Chem-101 to successfully reason about previously unseen situations, generating relevant (and potentially novel) attribute-aware social rules-of-thumb.

Key facts. Cited by 253 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Nov 2020.

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Citing papers per year: 2021: 17; 2022: 32; 2023: 59; 2024: 55; 2025: 40; 2026: 50.

253 papers.

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  1. 2023SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agentscited by 350
  2. 2023Large Language Model Alignment: A Surveycited by 241
  3. 2023Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theorycited by 218
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  5. 2023Evaluating the Moral Beliefs Encoded in LLMscited by 211
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  8. 2024Quantifying the Persona Effect in LLM Simulationscited by 164
  9. 2022Probing Pre-Trained Language Models for Cross-Cultural Differences in Valuescited by 147
  10. 2021Can Machines Learn Morality? The Delphi Experimentcited by 140
  11. 2021Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processingcited by 126
  12. 2022ProsocialDialog: A Prosocial Backbone for Conversational Agentscited by 109
38 more
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  2. 2023Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Dutiescited by 97
  3. 2022When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgmentcited by 93
  4. 2022The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systemscited by 92
  5. 2023NLPositionality: Characterizing Design Biases of Datasets and Modelscited by 91
  6. 2023A Survey on Fairness in Large Language Modelscited by 91
  7. 2024SOTOPIA-π: Interactive Learning of Socially Intelligent Language Agentscited by 89
  8. 2024SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safetycited by 75
  9. 2022Moral Mimicry: Large Language Models Produce Moral Rationalizations Tailored to Political Identitycited by 71
  10. 2023A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospectscited by 66
  11. 2024Massively Multi-Cultural Knowledge Acquisition & LM Benchmarkingcited by 63
  12. 2023Natural Language Reasoning, A Surveycited by 61
  13. 2023NormBank: A Knowledge Bank of Situational Social Normscited by 60
  14. 2021ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoningcited by 58
  15. 2024Fairness in Large Language Models: A Taxonomic Surveycited by 57
  16. 2024DailyDilemmas: Revealing Value Preferences of LLMs with Quandaries of Daily Lifecited by 57
  17. 2023TrustGPT: A Benchmark for Trustworthy and Responsible Large Language Modelscited by 56
  18. 2023The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Valuescited by 53
  19. 2023Everyone's Voice Matters: Quantifying Annotation Disagreement Using Demographic Informationcited by 52
  20. 2023Knowledge of cultural moral norms in large language modelscited by 51
  21. 2022NormSAGE: Multi-Lingual Multi-Cultural Norm Discovery from Conversations On-the-Flycited by 48
  22. 2024NormAd: A Framework for Measuring the Cultural Adaptability of Large Language Modelscited by 47
  23. 2024Diverging Preferences: When do Annotators Disagree and do Models Know?cited by 47
  24. 2024ALI-Agent: Assessing LLMs' Alignment with Human Values via Agent-based Evaluationcited by 46
  25. 2024Language Model Alignment in Multilingual Trolley Problemscited by 46
  26. 2023From Instructions to Intrinsic Human Values -- A Survey of Alignment Goals for Big Modelscited by 45
  27. 2023MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Taskscited by 44
  28. 2024Evaluating Cultural and Social Awareness of LLM Web Agentscited by 43
  29. 2022ClarifyDelphi: Reinforced Clarification Questions with Defeasibility Rewards for Social and Moral Situationscited by 36
  30. 2023Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories?cited by 36
  31. 2023Chinese Open Instruction Generalist: A Preliminary Releasecited by 35
  32. 2021ValueNet: A New Dataset for Human Value Driven Dialogue Systemcited by 34
  33. 2022Speaking Multiple Languages Affects the Moral Bias of Language Modelscited by 34
  34. 2023COBRA Frames: Contextual Reasoning about Effects and Harms of Offensive Statementscited by 34
  35. 2023EtiCor: Corpus for Analyzing LLMs for Etiquettescited by 33
  36. 2024Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statementscited by 33
  37. 2024KorNAT: LLM Alignment Benchmark for Korean Social Values and Common Knowledgecited by 33
  38. 2021Misinfo Reaction Frames: Reasoning about Readers' Reactions to News Headlinescited by 32

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