%0 Computer Program
%A Liscio, Enrico
%A Araque, Oscar
%A Gatti, Lorenzo
%A Constantinescu, Ionut
%A Jonker, C.M. (Catholijn)
%A Kalimeri, Kyriaki
%A Murukannaiah, Pradeep K.
%D 2023
%T What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric - code
%U 
%R 10.4121/1e71138c-be26-4652-971a-48a84837df8e.v1
%K NLP
%K Morality
%K Ethics
%K XAI
%K natural language processing
%K explainable artificial intelligence
%X <p>Code for the paper "What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric", published at ACL '23. This code implements Tomea, an Explainable AI method for investigating the difference in how language models represent morality across domains. Given a pair of datasets and models trained on the datasets, Tomea generates 10 m-distances and one d-distance to measure the difference between the datasets, based on the SHAP method. We make pairwise comparisons of seven models trained on the MFTC datasets (available at this DOI: 10.4121/646b20e3-e24f-452d-938a-bcb6ce30913c<strong>).</strong></p>
%I 4TU.ResearchData