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        Chapter Una nuova svolta negli studi letterari: la convergenza tra computazione, cognizione ed evoluzione

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        Author(s)
        Ciotti, Fabio
        Language
        Italian
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        Abstract
        Distant reading, an empirical and quantitative approach in literary studies proposed by Franco Moretti, has raised a lively debate and attracted criticisms from "traditional literary scholars." An important reason behind these criticisms is the need for solid theoretical foundations: distant reading is perhaps the first methodology in literary studies that do not include a specific theory of literature, an ontology of the literary. Much of the work in the field derives its theoretical frameworks from the literary theories of the twentieth-century tradition, based on the assumption that literary texts can be understood through reading and interpretation. A large-scale quantitative approach to literary and cultural phenomena is mainly incompatible with "the hermeneutic attitude" and traditional theories. Therefore, I propose a convergence with cognitive and bio-evolutionary approaches to literature and studies of cultural evolution and a shift from "interpretation" to "explanation" as the goal of computational literary studies.
        URI
        https://library.oapen.org/handle/20.500.12657/62737
        Keywords
        Computational literary studies; cognitive literary studies; cultural evolution; cultural analytics; distant reading
        DOI
        10.36253/979-12-215-0045-5.04
        ISBN
        9791221500455, 9791221500455
        Publisher
        Firenze University Press
        Publisher website
        https://www.fupress.com/
        Publication date and place
        Florence, 2022
        Series
        Moderna/Comparata, 41
        Classification
        Biography, Literature and Literary studies
        Pages
        18
        Rights
        https://creativecommons.org/licenses/by/4.0/
        • Imported or submitted locally

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        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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