JOURNAL ARTICLE
Female Protagonism and Multilingualism in Spanish Byzantine Novels Analysed Using Character Networks.
Published In: International Journal of Humanities & Arts Computing: A Journal of Digital Humanities, 2023, v. 17, n. 2. P. 168 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Palenzuela, José Luis Losada 3 of 3
Abstract
The rediscovery of Greek novels in Europe, in particular Heliodorus' Aethiopica, together with its literary emulations by Lope de Vega or Miguel de Cervantes, had a deep impact in the renewal of motifs, fictional devices and character descriptions, for example the explicit or implicit presence of foreign languages or the predominance of female characters. The analysis seeks to quantitatively identify the multilingual character and the position of the female protagonists in novels using network analysis. We have approached both aspects from a twofold methodological perspective – first, using taxonomies that help to describe more precisely the concept of multilingualism for quantitative studies; second, making use of measures of centrality to locate the protagonist. Taking into consideration various network metrics together with the language attribution, we can compare the correlation between character importance and languages. The results validate the hypothesis that the novels show a strong thematization of foreign languages, but the female heroines fall behind their male counterparts in protagonism. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Humanities & Arts Computing: A Journal of Digital Humanities. 2023/10, Vol. 17, Issue 2, p168
- Document Type:Article
- Subject Area:History
- Publication Date:2023
- ISSN:1753-8548
- DOI:10.3366/ijhac.2023.0311
- Accession Number:172914060
- Copyright Statement:Copyright of International Journal of Humanities & Arts Computing: A Journal of Digital Humanities is the property of Edinburgh University Press 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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