To the best of our knowledge, this is the first work to target affective dimensions in pre-trained contextualized word embeddings.
whereas the output of a persona model is distributions over personas and vocabulary, our system outputs scores along known dimensions of power, agency, and sentiment, which are easy to interpret and visualize.