• Can An Algorithm Be Disturbed?: Machine Learning, Intrinsic Criticism, and the Digital Humanities

    Author(s):
    James E. Dobson (see profile)
    Date:
    2015
    Group(s):
    TC Digital Humanities, TM Literary Criticism
    Subject(s):
    Digital humanities, Methodology
    Item Type:
    Article
    Tag(s):
    digital reading, hermeneutics, machine learning, Literary theory
    Permanent URL:
    http://dx.doi.org/10.17613/M6QW2C
    Abstract:
    This essay positions the use of machine learning within the digital humanities as part of a wider movement that nostalgically seeks to return literary criticism to the structuralist era, to a moment characterized by belief in systems, structure, and the transparency of language. It argues that the scientific criticism of the present attempts to separate methodology from interpretation and in the process it has deemphasized the degree to which methodology also participates in interpretation. This essay returns to the deconstructive critique of structuralism in order to highlight the ways in which numerous interpretive decisions are suppressed in the pre-processing of text and in the use of machine learning algorithms.
    Metadata:
    xml
    Published as:
    Journal article     Show details
    Publisher:
    Johns Hopkins University Press and West Chester University
    Pub. Date:
    October 2015
    Journal:
    College Literature: A Journal of Critical Literary Studies
    Volume:
    42
    Issue:
    4
    Page Range:
    543 - 564
    ISSN:
    0093-3139
    Status:
    Published
    License:
    All Rights Reserved

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