Uncovering Values: Detecting Latent Moral Content from Natural Language with Explainable and Non-Trained Methods
Luigi Asprino, Luana Bulla, Stefano De Giorgis, Aldo Gangemi, Ludovica Marinucci, Misael Mongiovi
Abstract
Moral values as commonsense norms shape our everyday individual and community behavior. The possibility to extract moral attitude rapidly from natural language is an appealing perspective that would enable a deeper understanding of social interaction dynamics and the individual cognitive and behavioral dimension. In this work we focus on detecting moral content from natural language and we test our methods on a corpus of tweets previously labeled as containing moral values or violations, according to Moral Foundation Theory. We develop and compare two different approaches: (i) a frame-based symbolic value detector based on knowledge graphs and (ii) a zero-shot machine learning model fine-tuned on a task of Natural Language Inference (NLI) and a task of emotion detection. The final outcome from our work consists in two approaches meant to perform without the need for prior training process on a moral value detection task.- Anthology ID:
- 2022.deelio-1.4
- Volume:
- Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland and Online
- Editors:
- Eneko Agirre, Marianna Apidianaki, Ivan Vulić
- Venue:
- DeeLIO
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 33–41
- Language:
- URL:
- https://aclanthology.org/2022.deelio-1.4
- DOI:
- 10.18653/v1/2022.deelio-1.4
- Cite (ACL):
- Luigi Asprino, Luana Bulla, Stefano De Giorgis, Aldo Gangemi, Ludovica Marinucci, and Misael Mongiovi. 2022. Uncovering Values: Detecting Latent Moral Content from Natural Language with Explainable and Non-Trained Methods. In Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures, pages 33–41, Dublin, Ireland and Online. Association for Computational Linguistics.
- Cite (Informal):
- Uncovering Values: Detecting Latent Moral Content from Natural Language with Explainable and Non-Trained Methods (Asprino et al., DeeLIO 2022)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2022.deelio-1.4.pdf
- Code
- stendoipanni/moraldilemmas
- Data
- DBpedia