Which Argumentative Aspects of Hate Speech in Social Media can be reliably identified?
Damián Ariel Furman, Pablo Torres, José A. Rodríguez, Laura Alonso Alemany, Diego Letzen, Vanina Martínez
Abstract
The expansion of Large Language Models (LLMs) into more serious areas of application, involving decision-making and the forming of public opinion, calls for a more thoughtful treatment of texts. Augmenting them with explicit and understandable argumentative analysis could foster a more reasoned usage of chatbots, text completion mechanisms or other applications. However, it is unclear which aspects of argumentation can be reliably identified and integrated by them. In this paper we propose an adaptation of Wagemans (2016)’s Periodic Table of Arguments to identify different argumentative aspects of texts, with a special focus on hate speech in social media. We have empirically assessed the reliability with which each of these aspects can be automatically identified. We analyze the implications of these results, and how to adapt the proposal to obtain reliable representations of those that cannot be successfully identified.- Anthology ID:
- 2023.dmr-1.13
- Volume:
- Proceedings of the Fourth International Workshop on Designing Meaning Representations
- Month:
- June
- Year:
- 2023
- Address:
- Nancy, France
- Editors:
- Julia Bonn, Nianwen Xue
- Venues:
- DMR | WS
- SIG:
- SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 136–153
- Language:
- URL:
- https://aclanthology.org/2023.dmr-1.13
- DOI:
- Cite (ACL):
- Damián Ariel Furman, Pablo Torres, José A. Rodríguez, Laura Alonso Alemany, Diego Letzen, and Vanina Martínez. 2023. Which Argumentative Aspects of Hate Speech in Social Media can be reliably identified?. In Proceedings of the Fourth International Workshop on Designing Meaning Representations, pages 136–153, Nancy, France. Association for Computational Linguistics.
- Cite (Informal):
- Which Argumentative Aspects of Hate Speech in Social Media can be reliably identified? (Furman et al., DMR-WS 2023)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2023.dmr-1.13.pdf