Abstract
In computational literary studies, the challenging task of predicting quality or reader-appreciation of narrative texts is confounded by volatile definitions of quality and the vast feature space that may be considered in modeling. In this paper, we explore two different types of feature sets: stylistic features on one hand, and semantic features on the other. We conduct experiments on a corpus of 9,089 English language literary novels published in the 19th and 20th century, using GoodReads’ ratings as a proxy for reader-appreciation. Examining the potential of both approaches, we find that some types of books are more predictable in one model than in the other, which may indicate that texts have different prominent characteristics (stylistic complexity, a certain narrative progression at the sentiment-level).- Anthology ID:
- 2023.ranlp-1.80
- Volume:
- Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
- Month:
- September
- Year:
- 2023
- Address:
- Varna, Bulgaria
- Editors:
- Ruslan Mitkov, Galia Angelova
- Venue:
- RANLP
- SIG:
- Publisher:
- INCOMA Ltd., Shoumen, Bulgaria
- Note:
- Pages:
- 739–747
- Language:
- URL:
- https://aclanthology.org/2023.ranlp-1.80
- DOI:
- Cite (ACL):
- Pascale Moreira and Yuri Bizzoni. 2023. Dimensions of Quality: Contrasting Stylistic vs. Semantic Features for Modelling Literary Quality in 9,000 Novels. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 739–747, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
- Cite (Informal):
- Dimensions of Quality: Contrasting Stylistic vs. Semantic Features for Modelling Literary Quality in 9,000 Novels (Moreira & Bizzoni, RANLP 2023)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/2023.ranlp-1.80.pdf