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