Understanding Interpersonal Conflict Types and their Impact on Perception Classification
This work addresses the understanding of interpersonal conflict and social norms, but it is incremental as it builds on existing typologies and focuses on a specific domain.
The researchers tackled the problem of predicting whether an individual's actions are perceived as right or wrong in interpersonal conflicts by creating a new annotated dataset and building a classifier, with analyses revealing differences in conflict content based on participant relationships.
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.