2022
Journal article  Open Access

Syllabic quantity patterns as rhythmic features for Latin authorship attribution

Corbara S., Moreo A., Sebastiani F.

Syllabic quantity  Authorship analysis  Authorship attribution  Latin 

It is well known that, within the Latin production of written text, peculiar metric schemes were followed not only in poetic compositions, but also in many prose works. Such metric patterns were based on so-called syllabic quantity, that is, on the length of the involved syllables, and there is substantial evidence suggesting that certain authors had a preference for certain metric patterns over others. In this research we investigate the possibility to employ syllabic quantity as a base for deriving rhythmic features for the task of computational authorship attribution of Latin prose texts. We test the impact of these features on the authorship attribution task when combined with other topic-agnostic features. Our experiments, carried out on three different datasets using support vector machines (SVMs) show that rhythmic features based on syllabic quantity are beneficial in discriminating among Latin prose authors.

Source: Journal of the Association for Information Science and Technology (2022). doi:10.1002/asi.24660

Publisher: Wiley-Blackwell


Metrics



Back to previous page
BibTeX entry
@article{oai:it.cnr:prodotti:468637,
	title = {Syllabic quantity patterns as rhythmic features for Latin authorship attribution},
	author = {Corbara S. and Moreo A. and Sebastiani F.},
	publisher = {Wiley-Blackwell},
	doi = {10.1002/asi.24660},
	journal = {Journal of the Association for Information Science and Technology},
	year = {2022}
}