Disentangling semantic and prosodic features of English poetry
Bibliographic Data
| ID | 7151802 |
|---|---|
| Authors | Wenyi Shang (0000-0002-1308-8422, University of Illinois Urbana-Champaign, corresponding author), Ted Underwood (0000-0001-8960-1846, University of Illinois Urbana-Champaign) |
| Year | 2025 |
| Volume | 40 |
| Issue | Supplement_1 |
| Pages | i87-i99 |
| Publication date | 2025-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Digital Scholarship in the Humanities (JOURNAL) |
| Journal identifiers | ISSN: 2055-7671 • E-ISSN: 2055-768X |
| Publisher | Oxford University Press (PUBLISHER • GB) |
| DOI | 10.1093/llc/fqae008 |
| OpenAlex | W4392185768 |
| Language | EN |
| Citations received | 1 |
| References cited | 11 |
The distinction between genre and form is still contested in literary studies. While scholars associated with the New Formalism are criticized for perceiving everything as a form, digital humanists tend to argue that everything is a genre. In this research, we employed machine learning models to classify 36,635 English poems in the Chadwyck-Healey Literature Collections into twenty-seven categories, focusing on their semantic features (lexicons) and prosodic features (meters and rhymes) independently. Our findings reveal that different categories of poetry are distinguished by different groups of characteristics, without a clear-cut division between those driven predominantly by semantic features and those driven predominantly by prosodic features. Instead, poetry categories manifest a combination of semantic and prosodic elements, spanning a spectrum of different strengths in both domains. These findings suggest that the colloquial distinction between “genre” and “form” is based on real differences between poetic categories, although those differences may not be quite as crisply binary as the vocabulary implies
Art · Formalism (music) · Linguistics · Literature · Natural language processing · Perplexity · Poetry · Vocabulary · Advanced Text Analysis Techniques · Artificial Intelligence · Computational and Text Analysis Methods · Computer Science · Digital Humanities and Scholarship · Philosophy · Psychology
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2025 - 2025 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |