@inproceedings{moreira-bizzoni-2023-dimensions,
title = "Dimensions of Quality: Contrasting Stylistic vs. Semantic Features for Modelling Literary Quality in 9,000 Novels",
author = "Moreira, Pascale and
Bizzoni, Yuri",
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2023.ranlp-1.80",
pages = "739--747",
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).",
}
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<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).</abstract>
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%0 Conference Proceedings
%T Dimensions of Quality: Contrasting Stylistic vs. Semantic Features for Modelling Literary Quality in 9,000 Novels
%A Moreira, Pascale
%A Bizzoni, Yuri
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F moreira-bizzoni-2023-dimensions
%X 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).
%U https://aclanthology.org/2023.ranlp-1.80
%P 739-747
Markdown (Informal)
[Dimensions of Quality: Contrasting Stylistic vs. Semantic Features for Modelling Literary Quality in 9,000 Novels](https://aclanthology.org/2023.ranlp-1.80) (Moreira & Bizzoni, RANLP 2023)
ACL