Sentimental Matters Predicting Literary Quality with Sentiment Analysis and Stylistic Features

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Abstract

The task of predicting reader appreciation or literary quality has been the object of several studies. It remains, however, a challenging problem in quantitative literary analyses and computational linguistics alike, as its definition can vary a lot depending on the genre of literary texts considered, the features adopted, and the annotation system employed. This paper attempts to evaluate the impact on reader appreciation, defined as online users’ ratings, of sentiment range and sentiment arc patterns versus traditional stylometric features. We run our experiments on a corpus of English-language literary fiction, showing that stylometric features alone are helpful in modelling literary quality, but can be outperformed by analysing the novels’ sentimental profile.

OriginalsprogEngelsk
TitelProceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
RedaktørerJeremy Barnes, Orphee De Clercq, Roman Klinger
Antal sider8
ForlagAssociation for Computational Linguistics
Publikationsdatojul. 2023
Sider11-18
ISBN (Elektronisk)978-1-959429-87-6
DOI
StatusUdgivet - jul. 2023
Begivenhed13th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2023 - Toronto, Canada
Varighed: 14 jul. 2023 → …

Konference

Konference13th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2023
Land/OmrådeCanada
ByToronto
Periode14/07/2023 → …
SponsorGoogle

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