mlsanityData to 7 Oct 2026

Understanding Interpersonal Conflict Types and their Impact on Perception Classification

arXiv 2208.08758 ↗First posted 18 Aug 2022cs.CLcited by 4

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Abstract (arXiv)

Studies on interpersonal conflict have a long history and contain many suggestions for conflict typology. We use this as the basis of a novel annotation scheme and release a new dataset of situations and conflict aspect annotations. We then build a classifier to predict whether someone will perceive the actions of one individual as right or wrong in a given situation. Our analyses include conflict aspects, but also generated clusters, which are human validated, and show differences in conflict content based on the relationship of participants to the author. Our findings have important implications for understanding conflict and social norms.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 10 of its 29 references that are in the map. First posted on arXiv 18 Aug 2022.

Builds on

10 of 29 references.

References · 10

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  3. 2021Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detectioncited by 258
  4. 2020Social Chemistry 101: Learning to Reason about Social and Moral Normscited by 253
  5. 2021MultiVerS: Improving scientific claim verification with weak supervision and full-document contextcited by 140
  6. 2020Scruples: A Corpus of Community Ethical Judgments on 32,000 Real-Life Anecdotescited by 100
  7. 2021Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators' Disagreementcited by 71
  8. 2021Analysis of Moral Judgement on Redditcited by 8
  9. 2022Explainable Patterns for Distinction and Prediction of Moral Judgement on Redditcited by 6
  10. 2021End-to-End Annotator Bias Approximation on Crowdsourced Single-Label Sentiment Analysiscited by 4

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Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 1.

4 papers.

  1. 2022Unifying Data Perspectivism and Personalization: An Application to Social Normscited by 22
  2. 2024Corpus Considerations for Annotator Modeling and Scalingcited by 8
  3. 2023NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Mediacited by 2
  4. 2025Examining the Utility of Self-disclosure Types for Modeling Annotators of Social Normscited by 0