What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric - supplemental material
doi: 10.4121/cd43b76a-850e-4222-ab81-5a20b7b1b93d
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.
The code to generate the results is available at this DOI: 10.4121/1e71138c-be26-4652-971a-48a84837df8e
The seven models are available at this DOI: 10.4121/646b20e3-e24f-452d-938a-bcb6ce30913c
- 2023-12-18 first online, published, posted
- Hybrid Intelligence Center (a 10-year programme funded by the Dutch Ministry of Education, Culture and Science through the Netherlands Organisation for Scientific Research).
- European Union's Horizon 2020 research and innovation program (grant code STG–677576) European Research Council
Universidad Politécnica de Madrid, Departamento de Ingeniería de Sistemas Telemáticos
University of Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Human Media Interaction (HMI)
ETH Zürich Department of Computer Science,
ISI Foundation, Data Science Laboratory
Leiden University, Leiden Institute of Advanced Computer Science
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