0602744 - ÚI 2025 RIV DE eng C - Conference Paper (international conference)
Tani Raffaelli, Giulio
Promises from an Inferential Approach in Classical Latin Authorship Attribution.
CHR 2024: Computational Humanities Research 2024: Proceedings of the Computational Humanities Research Conference 2024. Aachen: Technical University & CreateSpace Independent Publishing, 2024 - (Haverals, W.; Koolen, M.; Thompson, L.), s. 610-619. CEUR Workshop Proceedings, 3834. ISSN 1613-0073.
[CHR 2024: Computational Humanities Research Conference /5./. Aarhus (DK), 04.12.2024-06.12.2024]
Institutional support: RVO:67985807
Keywords : authorship attribution * inference * classical Latin * visualisation
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result website:
https://ceur-ws.org/Vol-3834/paper121.pdf

Applying stylometry to Authorship Attribution requires distilling the elements of an author’s style sufficient to recognise their mark in anonymous documents. Often, this is accomplished by contrasting the frequency of selected features in the authors’ works. A recent approach, CP2D, uses innovation processes to infer the author’s identity, accounting for their propensity to introduce new elements. In this paper, we apply CP2D to a corpus of Classical Latin texts to test its effectiveness in a new context and explore the additional insight it can offer the scholar. We show its effectiveness on a corpus of classical Latin texts and how—moving beyond maximum likelihood—we can visualise the stylistic relationships and gather additional information on the relationships among documents.
Permanent Link: https://hdl.handle.net/11104/0360031