High risk of political bias in black box emotion inference models.

ABSTRACT: This paper investigates the presence of political bias in emotion inference models used for sentiment analysis (SA). Machine learning models often reflect biases in their training data, impacting the validity of their outcomes. While previous research has highlighted gender and race biases, our study focuses on political bias-an underexplored, pervasive issue that can skew the interpretation of text data across many studies. We audit a Polish sentiment analysis model developed in our lab for bias. By analyzing valence predictions for names and sentences involving Polish politicians, we uncovered systematic differences influenced by political affiliations. Our findings suggest that annotations by human raters propagate political biases into the model's predictions. To prove it, we pruned th

SUBMITTER: Plisiecki H 

PROVIDER: S-EPMC11840103 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature