The Intersections between Sociology and STS: A Big Data Approach

Sociological Perspectives, vol. 66, pp. 868–887

Abstract

This paper charts the changing intersections between sociology and science and technology studies (STS) using computational textual analysis. We characterize this "quali-quantitative" approach as a Big Data method, as this calls attention to the commixture of textual and numeric data that characterizes Big Data. The term Big Data, too, calls attention to the increasing privatization of both data and data analytics tools. The data mining was done using a commercial analytics tool, IBM SPSS Modeler, that to the best of our knowledge has not yet been used for STS or sociological research. The identification of intersections occurred as part of a larger project to analyze political-economic and epistemic changes within STS, focusing on academic publishing. These epistemic changes were identified qualitatively, through 76 interviews with STS scholars, and quantitatively, through a computational analysis of three decades of STS journals (1990-2019).

Authors 3

1. Maria Amuchastegui corresponding

   York University

   Affiliation as printed

   York University, Toronto, ON, Canada

2. Kean Birch

   York University

   Affiliation as printed

   York University, Toronto, ON, Canada

3. Wolfgang Kaltenbrunner Aachen

   Leiden University

   Affiliation as printed

   Leiden University, Leiden, The Netherlands