Texts as data II: media content analysis

Abstract

This chapter discusses media content analysis, a method that applies quantitative and qualitative procedures to make inferences from text. Its main advantages are that it is unobtrusive, and that there is a plethora of media content available and accessible for research. The main challenge of the method is to develop a research design that promises valid inferences from text (meaning that ‘it captures what it sets out to capture’). Ignoring or not addressing such issues is the main reason for ethical concern. This chapter is based on the assumption that aside from more common methods like document analysis and interviews, media content analysis is also a valuable option for the study of media and communication policy. On the one hand, the method can grasp the public discourse about issues of media and communication policy. On the other hand, the data gathered by using this method offers much-needed evidence for policy-making. This chapter provides an overview on the steps of preparing and conducting a media content analysis, from the research design and sampling, to the process of coding, and the analysis of data. Two studies that employed media content analysis to investigate a topic relevant for media and communication policy are used as illustration. They have been selected because they clearly show the difference between the two main paradigmatic approaches to media content analysis: Von Pape, Trepte and Mothes’ (European Journal of Communication 32: 189–207, 2017) quantitative study follows the social science norm of being rigorously systematic, when exploring the discourse on privacy and new communication technology in Germany’s most popular and relevant newspapers and magazines. Young (Media International Australia 157: 79–90, 2015), in contrast, follows the humanities’ tradition of subjective interpretation, when examining the media policy reporting about the press council in Australia’s only national newspaper The Australian. Both approaches are valuable, and are ideally being used complementary, because they fill each others’ blind spots.