Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-31T19:00:31.416Z Has data issue: false hasContentIssue false
  • English
  • Français

Machine Learning and Human Perspective

Published online by Cambridge University Press:  02 October 2020

Ted Underwood
Get access Rights & Permissions [Opens in a new window]

Abstract

Numbers appear to have limited value for literary study, since our discipline is usually more concerned with exploring differences of interpretation than with describing the objective features of literary works. But it may be time to reexamine the assumption that numbers are useful only for objective description. Machine learning algorithms are actually bad at being objective and rather good at absorbing human perspectives implicit in the evidence used to train them. To dramatize perspectival uses of machine learning, I train models of genre on groups of books categorized by historical actors who range from Edwardian advertisers to contemporary librarians. Comparing the perspectives implicit in their choices casts new light on received histories of genre. Scientific romance and science fiction—whose shifting names have often suggested a fractured history—turn out to be more stable across two centuries than the genre we call fantasy. (TU)

Type
Special Topic: Varieties of Digital Humanities
Information
PMLA , Volume 135 , Issue 1: Special Topic Varieties of Digital Humanities , January 2020 , pp. 92 - 109
Copyright
Copyright © 2020 Ted Underwood

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Works Cited

Abbott, Andrew. “Things of Boundaries.” Social Research, Vol. 62, No. 4, 1995, pp. 857–82.Google Scholar
Alcoff, Linda Martín. Visible Identities. Oxford UP, 2006.CrossRefGoogle Scholar
Allison, Sarah, et al. “Quantitative Formalism: An Experiment.” Stanford Literary Lab, 15 Jan. 2011, litlab.stanford.edu/LiteraryLabPamphlet1.pdf.Google Scholar
Bailey, James O. Scientific Fiction in English, 1817-1914: A Study in Trends and Forms. 1934. U of North Carolina, PhD dissertation.Google Scholar
Bode, Katherine. “The Equivalence of ‘Close’ and ‘Distant’ Reading; or, Toward a New Object for Data-Rich Literary History.” Modern Language Quarterly, Vol. 78, No. 1, 2016, pp. 77–106.CrossRefGoogle Scholar
Bould, Mark, and Vint, Sherryl. The Routledge Concise History of Science Fiction. Routledge, 2011.CrossRefGoogle Scholar
Butler, Judith. Gender Trouble: Feminism and the Subversion of Identity. Routledge, 1990.Google Scholar
Buurma, Rachel Sagner, and Heffernan, Laura. “Search and Replace: Josephine Miles and the Origins of Distant Reading.” Modernism/Modernity, 11 Apr. 2018, modernismmodernity.org/forums/posts/search-and-replace.Google Scholar
Calvo Tello, José. “Genre Classification in Spanish Novels: A Hard Task for Humans and Machines?” European Association for Digital Humanities, Galway, Dec. 2018. EADH 2018, eadh2018.exordo.com/files/papers/46/final_draft/20181205_genre_classification_human_vs_machines.pdf.Google Scholar
Capitanu, Boris, et al. The HathiTrust Research Center Extracted Feature Dataset 1.0. HathiTrust Research Center, 2016, doi:10.13012/J8X63JT3.CrossRefGoogle Scholar
Catalogue of the Principal English Books in Circulation at Mudie's Select Library. Mudie's Select Library, 1911.Google Scholar
Clarke, Arthur C. Profiles of the Future: An Inquiry into the Limits of the Possible. Rev. ed., Harper and Row, 1973.Google Scholar
Cohen, Ralph. “History and Genre.” New Literary History, Vol. 17, No. 2, 1986, pp. 203–18.CrossRefGoogle Scholar
Dilthey, Wilhelm. The Formation of the Historical World in the Human Sciences. Princeton UP, 2002.Google Scholar
Drucker, Johanna. “Humanistic Theory and Digital Scholarship.” Debates in the Digital Humanities, edited by Gold, Matthew K., U of Minnesota P, 2012, dhdebates.gc.cuny.edu/debates/text/34.Google Scholar
Drucker, Johanna “Humanities Approaches to Graphical Display.” Digital Humanities Quarterly, Vol. 5, No. 1, 2011, www.digitalhumanities.org/dhq/vol/5/1/000091/000091.html.Google Scholar
Drucker, Johanna “Why Distant Reading Isn't.” PMLA, Vol. 132, No. 3, May 2017, pp. 628–35.Google Scholar
Dunning, Ted. “Accurate Methods for the Statistics of Surprise and Coincidence.” Computational Linguistics, Vol. 19, No. 1, 1993, pp. 61–74.Google Scholar
Eliot, George. The Mill on the Floss. 3 vols., William Blackwood, 1860.Google Scholar
Evans, Elizabeth F., and Wilkens, Matthew. “Nation, Ethnicity, and the Geography of British Fiction.” Journal of Cultural Analytics, 13 July 2018, culturalanalytics.org/2018/07/nation-ethnicity-and-the-geography-of-british-fiction-1880-1940/.CrossRefGoogle Scholar
Fish, Stanley. “What Is Stylistics and Why Are They Saying Such Terrible Things about It?” Approaches to Poetics, edited by Chatman, Seymour, Columbia UP, 1973, pp. 109–52.Google Scholar
Galloway, Alexander R. “Everything Is Computational.” Los Angeles Review of Books, 27 June 2013, lareviewofbooks.org/article/franco-morettis-distant-reading-a-symposium/.Google Scholar
Goldstone, Andrew. “The Doxa of Reading.” PMLA, Vol. 132, No. 3, May 2017, pp. 636–42.Google Scholar
Klein, Lauren F. “Distant Reading after Moretti.” Arcade, 2019, arcade.stanford.edu/blogs/distant-reading-after-moretti.Google Scholar
Latham, Rob. “Sextrapolation in New Wave Science Fiction.” Science Fiction Studies, Vol. 33, No. 2, July 2006, pp. 251–74.Google Scholar
Le Guin, Ursula. The Left Hand of Darkness. Ace, 1986.Google Scholar
Liu, Alan. “The Meaning of the Digital Humanities.” PMLA, Vol. 128, No. 2, Mar. 2013, pp. 409–23.Google Scholar
Long, Hoyt, and So, Richard J. “Turbulent Flow: A Computational Model of World Literature.” Modern Language Quarterly, Vol. 77, No. 3, Sept. 2016, pp. 345–67.CrossRefGoogle Scholar
Moretti, Franco. Graphs, Maps, Trees: Abstract Models for Literary History. Verso, 2005.Google Scholar
Pedregosa, Fabian, et al. “Scikit-learn: Machine Learning in Python.” JMLR, Vol. 12, 2011, pp. 2825–30.Google Scholar
Piper, Andrew. “Think Small: On Literary Modeling.” PMLA, Vol. 132, No. 3, May 2017, pp. 651–58.Google Scholar
Posner, Miriam. “What's Next: The Radical, Unrealized Potential of Digital Humanities.” Miriam Posner, 27 July 2015, miriamposner.com/blog/whats-next-the-radical-unrealized-potential-of-digital-humanities/.Google Scholar
Richter, David. The Progress of Romance: Literary Historiography and the Gothic Novel. Ohio State UP, 1996.Google Scholar
Rieder, John. “On Defining SF, or Not: Genre Theory, SF, and History.” Science Fiction Studies, Vol. 37, No. 2, July 2010, pp. 191–209.Google Scholar
Scarborough, Dorothy. The Supernatural in Modern English Fiction. G. P. Putnam, 1917.Google Scholar
Smith, John K. “Quantitative versus Interpretive: The Problem of Conducting Social Inquiry.” New Directions for Program Evaluation, no. 19, 1983, pp. 27–51.CrossRefGoogle Scholar
So, Richard J. “All Models Are Wrong.” PMLA, Vol. 132, No. 3, May 2017, pp. 668–73.Google Scholar
Stableford, Brian. Scientific Romance in Britain, 1890-1950. Fourth Estate, 1985.Google Scholar
Suvin, Darko. Metamorphoses of Science Fiction: On the Poetics and History of a Literary Genre. edited by Canavan, Gerry, Peter Lang, 2016.CrossRefGoogle Scholar
Tenen, Dennis Yi. “Toward a Computational Archaeology of Fictional Space.” New Literary History, Vol. 49, No. 1, 2018, pp. 119–47.CrossRefGoogle Scholar
Underwood, Ted. “Code and Data to Support ‘A Measured Perspective.‘” Zenodo, 1 Apr. 2018, doi:10.5281/zenodo.1210966.CrossRefGoogle Scholar
Underwood, Ted Distant Horizons: Digital Evidence and Literary Change. U of Chicago P, 2019.CrossRefGoogle Scholar
Underwood, Ted “The Historical Significance of Textual Distances.” Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Aug. 2018, pp. 60–69. ACL Anthology, aclweb.org/anthology/W18-4507.Google Scholar
Underwood, Ted, et al. “Replication Data for ‘The Transformation of Gender.‘” Harvard Dataverse, 2018, doi: 10.7910/DVN/ZM2MAN.CrossRefGoogle Scholar
Underwood, Ted “The Transformation of Gender in English-Language Fiction.” Cultural Analytics, 13 Feb. 2018, culturalanalytics.org/2018/02/the-transformation-of-gender-in-english-language-fiction/.CrossRefGoogle Scholar
Warhol, Robyn. “Genre Regenerated.” Introduction. The Work of Genre: Selected Essays from the English Institute, edited by Warhol, , English Institute / American Council of Learned Societies, 2011, hdl.handle.net/2027/heb.90055.0001.001.Google Scholar
Westfahl, Gary. Mechanics of Wonder: The Creation of the Idea of Science Fiction. Liverpool UP, 1999.Google Scholar
Wickham, Hadley. Ggplot2: Elegant Graphics for Data Analysis. Springer, 2009.CrossRefGoogle Scholar
Wolfe, Gary K. Evaporating Genres: Essays on Fantastic Literature. Wesleyan UP, 2011.Google Scholar