Large-scale quantitative profiling of the Old English verse tradition

Neidorf, Leonard; Krieger, Madison S.; Yakubek, Michelle; Chaudhuri, Pramit; Dexter, Joseph P.

doi:10.1038/s41562-019-0570-1

Cited by 28 publications

(6 citation statements)

References 31 publications

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“…In related work, we have developed a similar feature set for Ancient Greek, which has been used to classify prose and verse and, at a more finegrained level, epic and drama (Gianitsos et al, 2019). Our work on Old English has demonstrated the utility of related features for various literary and attribution studies (Neidorf et al, 2019). After extension of the current toolkit to Ancient Greek and Old English, we plan in due course to incorporate other underserved languages, in particular Bengali.…”

Section: Discussionmentioning

confidence: 99%

A Stylometry Toolkit for Latin Literature

Bolt¹,

Flynt²,

Chaudhuri

et al. 2019

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conferen

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Computational stylometry has become an increasingly important aspect of literary criticism, but many humanists lack the technical expertise or language-specific NLP resources required to exploit computational methods. We demonstrate a stylometry toolkit for analysis of Latin literary texts, which is freely available at www.qcrit.org/stylometry. Our toolkit generates data for a diverse range of literary features and has an intuitive pointand-click interface. The features included have proven effective for multiple literary studies and are calculated using custom heuristics without the need for syntactic parsing. As such, the toolkit models one approach to the user-friendly generation of stylometric data, which could be extended to other premodern and non-English languages underserved by standard NLP resources.

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Section: Discussionmentioning

confidence: 99%

A Stylometry Toolkit for Latin Literature

Bolt¹,

Flynt²,

Chaudhuri

et al. 2019

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conferen

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“…Following the work of Neidorf et al (2019), we used Genesis, one of the longest extant Old English poems, which is also known to be the work of multiple authors. A later poem, called Genesis B (30,406 characters long) is embedded within the approx.…”

Section: Genesis a Or B?mentioning

confidence: 99%

Computational authorship analysis of the homeric poems

Pavlopoulos

Konstantinidou

2022

Int J Digit Humanities

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Natural language modeling is used to predict or generate the next word or character of modern languages. Furthermore, statistical character-based language models have been found useful in authorship attribution analyses by studying the linguistic proximity of excerpts unknown to the model. In prior work, we modeled Homeric language and provided empirical findings regarding the authorship nature of the 48 Iliad and Odyssey books. Following this line of work, and considering the current philological views and trends, we break down the two poems further into smaller portions. By employing language modeling we identify outlying passages, indicating reduced linguistic affinity with the main body of the two works and, by extension, potentially different authorship. Our results show that some of the passages isolated as outliers by the language models were also identified as such by human researchers. We further test our methodology and models on texts of similar language and genre created by other authors, namely Hesiod’s “Theogony” and “Work and Days”.

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“…In this landscape the idea of employing prosodic features is not a new one. Of course, their most natural use is in studies focused on poetry, such as in the study of Neidorf et al (2019) on the Old English verse tradition, or in the already cited investigation by Forstall et al (2011) on the supposed influence of Catullus on Paul the Deacon's writings. Nevertheless, rhythmic or prosodic features have also been employed in authorship analysis of prose text.…”

Section: Related Workmentioning

confidence: 99%

Syllabic quantity patterns as rhythmic features for Latin authorship attribution

Corbara

Moreo

Sebastiani

2022

Asso for Info Science & Tech

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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.

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Large-scale quantitative profiling of the Old English verse tradition

Cited by 28 publications

References 31 publications

A Stylometry Toolkit for Latin Literature

A Stylometry Toolkit for Latin Literature

Computational authorship analysis of the homeric poems

Syllabic quantity patterns as rhythmic features for Latin authorship attribution

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