Analysing pathos in user-generated argumentative text
- Publication type
- C1
- Publication status
- Published
- Authors
- Evgrafova, N., Hoste, V., & Lefever, E.
- Editor
- Haithem Afli, Houda Bouamor, Cristina Blasi Casagran and Sahar Ghannay
- Series
- Proceedings of the Second Workshop on Natural Language Processing for Political Sciences @ LREC-COLING 2024
- Pagination
- 39-44
- Publisher
- ELRA and ICCL
- Conference
- Second Workshop on Natural Language Processing for Political Sciences @ LREC-COLING-2024 (PoliticalNLP 2024) (Turin, Italy)
- Download
- (.pdf)
- View in Biblio
- (externe link)
Abstract
While persuasion has been extensively examined in the context of politicians’ speeches, there exists a notable gap in the understanding of the pathos role in user-generated argumentation. This paper presents an exploratory study into the pathos dimension of user-generated arguments and formulates ideas on how pathos could be incorporated in argument mining. Using existing sentiment and emotion detection tools, this research aims to obtain insights into the role of emotion in argumentative public discussion on controversial topics, explores the connection between sentiment and stance, and detects frequent emotion-related words for a given topic.