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Attributing authorship in the noisy digitized correspondence of Jacob and Wilhelm Grimm
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Except where otherwise noted, this item's license is described as Udzielam licencji. Uznanie autorstwa 4.0 Międzynarodowa
Attributing authorship in the noisy digitized correspondence of Jacob and Wilhelm Grimm
Bibliographic description
| title: | Attributing authorship in the noisy digitized correspondence of Jacob and Wilhelm Grimm |
| author: | Franzini Greta, Kestemont Mike, Rotari Gabriela, Jander Melina, Ochab Jeremi  , Franzini Emily, Byszuk Joanna, Rybicki Jan
|
| journal title: | Frontiers in Digital Humanities |
| volume: | 5 |
| date of publication : | 2018 |
| article ID: | 4 |
| eISSN: |
2297-2668 |
| DOI: | |
| notes: | Publikacja w j. węgierskim: Szerzőazonosítás Jacob és Wilhelm Grimm zajos, digitalizált levelezésében, Digitális Bölcsészet vol. 5 (2021). DOI: 10.31400/dh-hun.2021.5.3144, https://ruj.uj.edu.pl/xmlui/handle/item/288895 |
| language: | English |
| journal language: | English |
| abstract in English: | This article presents the results of a multidisciplinary project aimed at better understanding the impact of different digitization strategies in computational text analysis. More specifically, it describes an effort to automatically discern the authorship of Jacob and Wilhelm Grimm in a body of uncorrected correspondence processed by HTR (Handwritten Text Recognition) and OCR (Optical Character Recognition), reporting on the effect this noise has on the analyses necessary to computationally identify the different writing style of the two brothers. In summary, our findings show that OCR digitization serves as a reliable proxy for the more painstaking process of manual digitization, at least when it comes to authorship attribution. Our results suggest that attribution is viable even when using training and test sets from different digitization pipelines. With regard to HTR, this research demonstrates that even though automated transcription significantly increases risk of text misclassification when compared to OCR, a cleanliness above $\approx$ 20% is already sufficient to achieve a higher-than-chance probability of correct binary attribution. |
| affiliation: | Wydział Filologiczny : Instytut Filologii Angielskiej, Wydział Fizyki, Astronomii i Informatyki Stosowanej : Instytut Fizyki im. Mariana Smoluchowskiego |
| type: | journal article |
| subtype: | academic paper |
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Except where otherwise noted, this item's license is described as Udzielam licencji. Uznanie autorstwa 4.0 Międzynarodowa
Projekt „Repozytorium otwartego dostępu do dorobku naukowego i dydaktycznego UJ” współfinansowany w ramach poddziałania 2.3.1 „Cyfrowe udostępnianie zasobów nauki” Programu Operacyjnego Polska Cyfrowa z Europejskiego Funduszu Rozwoju Regionalnego i budżetu państwa na podstawie umowy o dofinansowanie nr POPC.02.03.01-00-0030/17-00
