From Ends to Means: The Promise of Computational Text Analysis for Theoretically Driven Sociological Research

Abstract

As the field of computational text analysis within the social sciences is maturing, computational methods are no longer seen as ends in themselves, but rather as means toward answering theoretically motivated research questions. The objective of this special issue is to showcase such research - the use of novel computational methods in the service of advancing substantive scientific knowledge. In presenting the contributions to the issue, we discuss several insights that emerge from this work, which hold relevance not only for current and aspiring practitioners of computational text analysis, but also for its skeptics. These concern the central role of theory in designing and executing computational research, the selection of appropriate techniques from a rapidly growing methodological toolkit, the benefits—and risks—of methodological bricolage, and the necessity of validating all aspects of the research process. The result is a set of broad considerations concerning the effective application of computational methods to substantive questions, illustrated by eight exemplary empirical studies.

Laura K. Nelson

Assistant Professor of Sociology

I use computational methods to study social movements, culture, gender, institutions, and the history of feminism. I’m particularly interested in developing transparent and reproducible text analysis methods for sociology using open-source tools.