Gender and Politeness Perception: A Novel Approach for Exploring Annotations Disagreement

AbstractPoliteness is an important social phenomenon which influences the flow of conversations. Several studies proposed models to discover and analyze linguistic cues associated with (im)polite language. However, no prior work computationally studied how politeness perception interacts with other social dimensions such as gender. We propose a model for automatic discovery of linguistic patterns which correlate with disagreement in politeness annotations, specifically focusing on gender differences. The model discovers fine-grained context patterns of words which correlate with disagreement in politeness annotations between men and women annotators. We apply the proposed model on emails annotated for politeness. Results show women rate emails which contain formal cues (e.g. To whom it may concern) more polite than men annotators rate them, while men rate emails exhibiting informal language cues (e.g. haven’t seen my new swing) more polite than women annotators rate them. Our findings highlight the importance of studying politeness through multiple demographic perspectives.