Content Analysis

Abstract

Content analysis is a quantitative method that uses human coders to apply a set of valid measurement rules to reduce manifest features of content to numeric data in order to make replicable, generalizable inferences about that content. Because the method is applied to human artifacts, it has generic advantages that apply whether doing quantitative content analysis or qualitative textual or rhetorical analysis. For example, analyzing communication content is an unobtrusive research activity that is unaffected by self-report biases. However, it is critical to differentiate content analysis as a distinct, quantitative, social-scientific method using human coders from other methods of analyzing content: this is done in order to call attention to the method’s unique strengths and weaknesses. A weakness of content analysis is that assigning content to numeric categories loses some of the richness of human communication. A strength of content analysis is that it reduces complex communication phenomenon to numeric data, allowing researchers to study broader phenomenon than would be possible via methods that rely on close reading. Furthermore, probabilistic sampling allows researchers to draw inferences about a given communication phenomenon without observing all cases and processes. Reliability testing also helps ensure that results have greater precision and are replicable. Although content analysis developed out of the US scholarly community building on code breaking during the Second World War, it is now used around the world. However, most of the available texts in non-English languages are translations from texts originally written in English. The following sections provide references that give scholars, both novices and those who are experienced in using content analysis, a strong foundation in the method, especially as it applies to studying media content. The references focus on content analysis applied to theory, units of measurement, sampling, and reliability. They also suggest core texts and journals that are good outlets for content analysis scholarship. Compared to other methods based on measuring implicit attitudes (e.g., survey research), content analysis has been the subject of much less methodological research aimed at improving the method itself. So the following discussion also calls attention to those areas where more empirical research may help advance the method, providing young and experienced scholars alike an opportunity to make their own contributions to the method and improve measurement.