Good Secretaries, Bad Truck Drivers? Occupational Gender Stereotypes in Sentiment Analysis

This project investigated the presence of occupational gender stereotypes in sentiment analysis models. Such a task has implications for reducing implicit biases in these models, which are being applied to an increasingly wide variety of downstream tasks. We released a new gender-balanced dataset of 800 sentences pertaining to specific professions and proposed a methodology for using it as a test bench to evaluate sentiment analysis models. We evaluated the presence of occupational gender stereotypes in 3 different models using our approach, and explored their relationship with societal perceptions of occupations.