Dimensions of Interpersonal Dynamics in Text: Group Membership and Fine-grained Interpersonal Emotion. (arXiv:2209.06687v1 [cs.CL])

The ability of language to perpetuate inequality is most evident when
individuals refer to, or talk about, other individuals in their utterances.
While current studies of bias in NLP rely mainly on identifying hate speech or
bias towards a specific group, we believe we can reach a more subtle and
nuanced understanding of the interaction between bias and language use by
modeling the speaker, the text, and the target in the text. In this paper, we
introduce a dataset of …

arxiv dynamics emotion fine-grained text