The “Computational Turn”: An “Interdisciplinary Turn”?: A Systematic Review of Text as Data Approaches in Journalism Research

Abstract

Possibilities of applying automated content analysis in journalism research include, for example, machine learning to identify topics in journalistic coverage or measuring news diffusion via automated approaches. But how has the computational method been applied thus far? And what are consequences of the “computational turn” in communication research, especially concerning interdisciplinarity? Based on a systematic literature review, this article summarizes the use of automated content analysis in journalism research. Results illustrate an increasing use of the method by communication scientists as yet another indicator of methodological interdisciplinarity in communication research. However, there is little evidence of an increase in theoretical interdisciplinarity: Studies relying on computational methods do not increasingly refer to theories from other disciplines. With respect to practical interdisciplinarity, for instance collaborations, our discipline is by no means becoming more interdisciplinary. Instead, we find a shift in favor of technical disciplines. At least up to now, the “computational turn” in communication research should not be equated with an “interdisciplinary turn”.