@inproceedings{bizzoni-etal-2023-sentimental,
    title = "Sentimental Matters - Predicting Literary Quality by Sentiment Analysis and Stylometric Features",
    author = "Bizzoni, Yuri  and
      Moreira, Pascale  and
      Thomsen, Mads Rosendahl  and
      Nielbo, Kristoffer",
    editor = "Barnes, Jeremy  and
      De Clercq, Orph{\'e}e  and
      Klinger, Roman",
    booktitle = "Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, {\&} Social Media Analysis",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.wassa-1.2",
    doi = "10.18653/v1/2023.wassa-1.2",
    pages = "11--18",
    abstract = "Over the years, the task of predicting reader appreciation or literary quality has been the object of several studies, but it remains a challenging problem in quantitative literary studies and computational linguistics alike, as its definition can vary a lot depending on the genre, the adopted features and the annotation system. This paper attempts to evaluate the impact of sentiment arc modelling versus more classical stylometric features for user-ratings of novels. We run our experiments on a corpus of English language narrative literary fiction from the 19th and 20th century, showing that syntactic and surface-level features can be powerful for the study of literary quality, but can be outperformed by sentiment-characteristics of a text.",
}

Over the years, the task of predicting reader appreciation or literary quality has been the object of several studies, but it remains a challenging problem in quantitative literary studies and computational linguistics alike, as its definition can vary a lot depending on the genre, the adopted features and the annotation system. This paper attempts to evaluate the impact of sentiment arc modelling versus more classical stylometric features for user-ratings of novels. We run our experiments on a corpus of English language narrative literary fiction from the 19th and 20th century, showing that syntactic and surface-level features can be powerful for the study of literary quality, but can be outperformed by sentiment-characteristics of a text.
Bizzoni, Yuri Moreira, Pascale Thomsen, Mads Rosendahl Nielbo, Kristoffer
Sentimental Matters - Predicting Literary Quality by Sentiment Analysis and Stylometric Features