Abstract
The literary domain continues to pose a challenge for Sentiment Analysis methods, due to its particularly nuanced and layered nature. This paper explores the adequacy of different Sentiment Analysis tools - from dictionary-based approaches to state-of-the-art Transformers - for capturing valence and modelling sentiment arcs. We take Ernest Hemingway’s novel The Old Man and the Sea as a case study to address challenges inherent to literary language, compare Transformer and rule-based systems’ scores with human annotations, and shed light on the complexities of analyzing sentiment in narrative texts. Finally, we emphasize the potential of model ensembles.- Anthology ID:
- 2023.nlp4dh-1.25
- Volume:
- Proceedings of the Joint 3rd International Conference on Natural Language Processing for Digital Humanities and 8th International Workshop on Computational Linguistics for Uralic Languages
- Month:
- December
- Year:
- 2023
- Address:
- Tokyo, Japan
- Editors:
- Mika Hämäläinen, Emily Öhman, Flammie Pirinen, Khalid Alnajjar, So Miyagawa, Yuri Bizzoni, Niko Partanen, Jack Rueter
- Venues:
- NLP4DH | IWCLUL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 219–228
- Language:
- URL:
- https://aclanthology.org/2023.nlp4dh-1.25
- DOI:
- Cite (ACL):
- Yuri Bizzoni and Pascale Feldkamp. 2023. Comparing Transformer and Dictionary-based Sentiment Models for Literary Texts: Hemingway as a Case-study. In Proceedings of the Joint 3rd International Conference on Natural Language Processing for Digital Humanities and 8th International Workshop on Computational Linguistics for Uralic Languages, pages 219–228, Tokyo, Japan. Association for Computational Linguistics.
- Cite (Informal):
- Comparing Transformer and Dictionary-based Sentiment Models for Literary Texts: Hemingway as a Case-study (Bizzoni & Feldkamp, NLP4DH-IWCLUL 2023)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2023.nlp4dh-1.25.pdf