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Theorizing Data: A Typology of Effects

Mon, August 12, 10:30am to 12:10pm, Sheraton New York, Floor: Lower Level, Chelsea

Abstract

Big Data, algorithms, artificial intelligence... Multiple and overlapping concepts coexist to make sense of digital technologies of quantification and their impact on the social world. This article offers a theoretical framework to clarify the social and organizational effects of data, online and offline. Specifically, I provide a typology of five different mechanisms through which data- driven procedures operate: comparison, dragnet, triage, extraction, and prominence. After drawing on analog and digital examples to illustrate these processes, I put this framework to use by turning to three empirical cases that involve data-driven software programs: Chartbeat in web journalism, COMPAS in criminal justice, and Predictim in babysitter hiring. I analyze these cases through the typology offered above. The article concludes by calling for more robust theoretical integration in the uses of data both as a method and as an object of study.

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