TY - DATA
T1 - What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric - supplemental material
PY - 2023/12/18
AU - Enrico Liscio
AU - Oscar Araque
AU - Lorenzo Gatti
AU - Ionut Constantinescu
AU - C.M. (Catholijn) Jonker
AU - Kyriaki Kalimeri
AU - Pradeep K. Murukannaiah
UR - 
DO - 10.4121/cd43b76a-850e-4222-ab81-5a20b7b1b93d.v1
KW - NLP
KW - Morality
KW - Ethics
KW - XAI
KW - natural language processing
N2 - <p>Raw results and crowd task material 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 repository contains two main folders. First, the instructions and informed consent used to perform the crowd study described in the paper, where crowd workers are asked to compare word bubbles describing moral values in a domain. Second, the results of the pairwise comparisons performed with the seven models trained on the MFTC datasets and the comparison of the results with the crowd annotations.</p><p>The code to generate the results is available at this DOI: 10.4121/1e71138c-be26-4652-971a-48a84837df8e</p><p>The seven models are available at this DOI: 10.4121/646b20e3-e24f-452d-938a-bcb6ce30913c</p>
ER -