Print Email Facebook Twitter Estimating the transferability of state-of-the-art models in predicting moral values Title Estimating the transferability of state-of-the-art models in predicting moral values Author Dondera, Alin (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Intelligent Systems) Contributor Liscio, E. (mentor) Murukannaiah, P.K. (mentor) Marroquim, Ricardo (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2021-07-02 Abstract Moral values play a crucial role in our decision-making process by defining what is right and wrong. With the emergence of political activism and moral discourse on social media, and the latest developments in Natural Language Processing, we are looking at an opportunity to analyze moral values to observe trends as they form. Recent studies have extensively examined the performance of different NLP models for estimating moral values from text, but none of them has tackled the problem of transfer learning. Our study provides a comprehensive look into the cross-domain performance of three state-of-the-art models. We find that BERT, the current most used model in Natural Language Processing, offers the best results. For reproducibility, we publicly release our code on GitHub. Subject Moral valuesMoral Foundation TheoryTransfer learningDomain AdaptationNatural Language Processing To reference this document use: http://resolver.tudelft.nl/uuid:47fe5f24-44ff-42af-9753-0eb3903846c9 Embargo date 2022-12-31 Part of collection Student theses Document type bachelor thesis Rights © 2021 Alin Dondera Files PDF Research_Project_2021_Ali ... _final.pdf 188.16 KB Close viewer /islandora/object/uuid:47fe5f24-44ff-42af-9753-0eb3903846c9/datastream/OBJ/view