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Found 6 papers, 1 papers with code
Predicting Literary Quality How Perspectivist Should We Be?
Approaches in literary quality tend to belong to two main grounds: one sees quality as completely subjective, relying on the idiosyncratic nature of individual perspectives on the apperception of beauty; the other is ground-truth inspired, and attempts to find one or two values that predict something like an objective quality: the number of copies sold, for example, or the winning of a prestigious prize.
$S^3$ -- Semantic Signal Separation
Topic models are useful tools for discovering latent semantic structures in large textual corpora.
Good Books are Complex Matters: Gauging Complexity Profiles Across Diverse Categories of Perceived Literary Quality
In this study, we employ a classification approach to show that different categories of literary "quality" display unique linguistic profiles, leveraging a corpus that encompasses titles from the Norton Anthology, Penguin Classics series, and the Open Syllabus project, contrasted against contemporary bestsellers, Nobel prize winners and recipients of prestigious literary awards.
Danish Foundation Models
Large language models, sometimes referred to as foundation models, have transformed multiple fields of research.
Sentiment Dynamics of Success: Fractal Scaling of Story Arcs Predicts Reader Preferences
We explore the correlation between the sentiment arcs of H. C. Andersen's fairy tales and their popularity, measured as their average score on the platform GoodReads.
DaCy: A Unified Framework for Danish NLP
In addition, we conduct a series of tests for biases and robustness of Danish NLP pipelines through augmentation of the test set of DaNE.
Ranked #1 on
Dependency Parsing
on DaNE
