Computational Modeling of Stereotype Content in Text.

ABSTRACT: Stereotypes are encountered every day, in interpersonal communication as well as in entertainment, news stories, and on social media. In this study, we present a computational method to mine large, naturally occurring datasets of text for sentences that express perceptions of a social group of interest, and then map these sentences to the two-dimensional plane of perceived warmth and competence for comparison and interpretation. This framework is grounded in established social psychological theory, and validated against both expert annotation and crowd-sourced stereotype data. Additionally, we present two case studies of how the model might be used to answer questions using data "in-the-wild," by collecting Twitter data about women and older adults. Using the data about women

SUBMITTER: Fraser KC 

PROVIDER: S-EPMC9063736 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature