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    <titleInfo>
        <title>A Computational Analysis of the Voices of Shakespeare’s Characters</title>
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        <namePart type="given">Liviu</namePart>
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        <namePart type="given">Sabina</namePart>
        <namePart type="family">Uban</namePart>
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            <title>Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing</title>
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            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
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    <abstract>In this paper we propose a study of a relatively novel problem in authorship attribution research: that of classifying the stylome of characters in a literary work. We choose as a case study the plays of William Shakespeare, presumably the most renowned and respected dramatist in the history of literature. Previous research in the field of authorship attribution has shown that the writing style of an author can be characterized and distinguished from that of other authors automatically. The question we propose to answer is a related but different one: can the styles of different characters be distinguished? We aim to verify in this way if an author managed to create believable characters with individual styles, and focus on Shakespeare’s iconic characters. We present our experiments using various features and models, including an SVM and a neural network, show that characters in Shakespeare’s plays can be classified with up to 50% accuracy.</abstract>
    <identifier type="citekey">dinu-uban-2023-computational</identifier>
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        <url>https://aclanthology.org/2023.ranlp-1.33</url>
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%0 Conference Proceedings
%T A Computational Analysis of the Voices of Shakespeare’s Characters
%A Dinu, Liviu P.
%A Uban, Ana Sabina
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F dinu-uban-2023-computational
%X In this paper we propose a study of a relatively novel problem in authorship attribution research: that of classifying the stylome of characters in a literary work. We choose as a case study the plays of William Shakespeare, presumably the most renowned and respected dramatist in the history of literature. Previous research in the field of authorship attribution has shown that the writing style of an author can be characterized and distinguished from that of other authors automatically. The question we propose to answer is a related but different one: can the styles of different characters be distinguished? We aim to verify in this way if an author managed to create believable characters with individual styles, and focus on Shakespeare’s iconic characters. We present our experiments using various features and models, including an SVM and a neural network, show that characters in Shakespeare’s plays can be classified with up to 50% accuracy.
%U https://aclanthology.org/2023.ranlp-1.33
%P 295-300

Markdown (Informal)

[A Computational Analysis of the Voices of Shakespeare’s Characters](https://aclanthology.org/2023.ranlp-1.33) (Dinu & Uban, RANLP 2023)

• A Computational Analysis of the Voices of Shakespeare’s Characters (Dinu & Uban, RANLP 2023)

ACL

• Liviu P. Dinu and Ana Sabina Uban. 2023. A Computational Analysis of the Voices of Shakespeare’s Characters. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 295–300, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.