Debates over the transformative power of “Big Data” are all the rage at the moment. While the mass collection of data made possible by new technologies has been alternately hyped, hailed, and ... read more
Debates over the transformative power of “Big Data” are all the rage at the moment. While the mass collection of data made possible by new technologies has been alternately hyped, hailed, and criticized in the media and research, few contest that “[t]he era of Big Data has begun” (boyd and Crawford, 2012). In this class, we will explore how it began. By turning to a period in U.S. literary history that coincided with the radical expansion of quantitative methods into social and psychological phenomena, we will examine what role fiction played in the construction, circulation, and negotiation of data as a form of social knowledge. While literature is usually seen as antagonistic to quantification, the naturalist movement in the late nineteenth- and early twentieth centuries was not only sympathetic to scientific methods but was even first conceptualized as an instrument for the generation of social data. How did American literary naturalism reflect the contemporaneous zest for numbers: for counting, measuring, classifying, and categorizing? How did the logic of aggregation in the social sciences influence narrative strategies in naturalist texts? And to what extent did such strategies function to interrogate or disseminate a modern epistemology of data? Addressing these questions and others that bear on the relationship between data and fiction, the goal of the class will be to shed light on the literary and social fictions underlying the construction and application of “data” in society.
We will read stories and novels by the following authors: Stephen Crane, Frank Norris, Edith Wharton, Jack London, Charlotte Perkins Gilman, Paul Laurence Dunbar, and Theodore Dreiser.