Abstract
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.- Anthology ID:
- 2022.nlpcss-1.10
- Volume:
- Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS)
- Month:
- November
- Year:
- 2022
- Address:
- Abu Dhabi, UAE
- Venue:
- NLP+CSS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 79–88
- Language:
- URL:
- https://aclanthology.org/2022.nlpcss-1.10
- DOI:
- Cite (ACL):
- Charles Welch, Joan Plepi, Béla Neuendorf, and Lucie Flek. 2022. Understanding Interpersonal Conflict Types and their Impact on Perception Classification. In Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS), pages 79–88, Abu Dhabi, UAE. Association for Computational Linguistics.
- Cite (Informal):
- Understanding Interpersonal Conflict Types and their Impact on Perception Classification (Welch et al., NLP+CSS 2022)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/2022.nlpcss-1.10.pdf