What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric

In collaboration with Enrico Liscio,Catholijn Jonker, Pradeep Kumar Murukannaiah from TU Delft

Oscar Araque from Universidad Politecnica de Madrid

Lorenzo Gatti from University of Twente, and 

Ionut Constantinescu, from ETH Zurich.

Moral rhetoric influences our judgement. Although social scientists recognize moral expression as domain specific, there are no systematic methods for analyzing whether a text classifier learns the domain-specific expression of moral language or not.

We propose Tomea, a method to compare a supervised classifier’s representation of moral rhetoric across domains. Tomea enables quantitative and qualitative comparisons of moral rhetoric via an interpretable exploration of similarities and differences across moral concepts and domains. We apply Tomea on moral narratives in thirty-five thousand tweets from seven domains. We extensively evaluate the method via a crowd study, a series of cross-domain moral classification comparisons, and a qualitative analysis of cross-domain moral expression.

Read the full article published on ACL Anthology 2023