JOURNAL ARTICLE

Stylometric analysis of French plays of the 17th century.

  • Published In: Digital Scholarship in the Humanities, 2024, v. 39, n. 2. P. 736 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Savoy, Jacques 3 of 3

Abstract

This article investigates the authorship attribution of sixty-six French comedies in verse from the 17th century, traditionally attributed to seventeen supposed authors, by testing the "signature hypothesis"—the assumption that the name on the cover corresponds to the true author. Using two stylometric methods, the intertextual distance and an improved Delta method (which estimates attribution probabilities), the study compares these plays alongside two additional corpora of French and Italian novels to validate the methods. The findings reveal numerous strong stylistic similarities between plays attributed to different authors, particularly involving figures who were primarily actors rather than playwrights, suggesting that the signature hypothesis does not hold for much of this corpus. While some authors' works (e.g., Rotrou, Racine) show distinct styles supporting their attribution, the overall results indicate that many plays likely share authorship or stylistic influence, complicating definitive author identification based solely on textual analysis. The study acknowledges limitations, including the exclusion of external historical evidence and the possibility of collaborative authorship.

Additional Information

  • Source:Digital Scholarship in the Humanities. 2024/06, Vol. 39, Issue 2, p736
  • Document Type:Article
  • Subject Area:Communication and Mass Media
  • Publication Date:2024
  • ISSN:2055-768X
  • DOI:10.1093/llc/fqae011
  • Accession Number:177947256
  • Copyright Statement:Copyright of Digital Scholarship in the Humanities is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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