# Understanding Interpersonal Conflict Types and their Impact on Perception Classification

arXiv: https://arxiv.org/abs/2208.08758 · HTML: https://mlsanity.com/paper/2208.08758/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 29 references that are in the map.
- First posted on arXiv 18 Aug 2022.

## Builds on (most cited first, 10 of 10)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection](https://mlsanity.com/paper/2111.07997/) (2021)
- [Social Chemistry 101: Learning to Reason about Social and Moral Norms](https://mlsanity.com/paper/2011.00620/) (2020)
- [MultiVerS: Improving scientific claim verification with weak supervision and full-document context](https://mlsanity.com/paper/2112.01640/) (2021)
- [Scruples: A Corpus of Community Ethical Judgments on 32,000 Real-Life Anecdotes](https://mlsanity.com/paper/2008.09094/) (2020)
- [Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators' Disagreement](https://mlsanity.com/paper/2109.13563/) (2021)
- [Analysis of Moral Judgement on Reddit](https://mlsanity.com/paper/2101.07664/) (2021)
- [Explainable Patterns for Distinction and Prediction of Moral Judgement on Reddit](https://mlsanity.com/paper/2201.11155/) (2022)
- [End-to-End Annotator Bias Approximation on Crowdsourced Single-Label Sentiment Analysis](https://mlsanity.com/paper/2111.02326/) (2021)

## Built on by (most cited first, 4 of 4)

- [Unifying Data Perspectivism and Personalization: An Application to Social Norms](https://mlsanity.com/paper/2210.14531/) (2022)
- [Corpus Considerations for Annotator Modeling and Scaling](https://mlsanity.com/paper/2404.02340/) (2024)
- [NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Media](https://mlsanity.com/paper/2301.11004/) (2023)
- [Examining the Utility of Self-disclosure Types for Modeling Annotators of Social Norms](https://mlsanity.com/paper/2512.16034/) (2025)

## 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.