One type of research that has played a major role in the Pew Research Center’s work over time, particularly in our ongoing work focused on journalism and news, has been content analysis, a tool that allows us to look at the way messages change over time and vary across mediums and outlets.
Content analysis has been defined as “the systematic, objective, quantitative analysis of message characteristics.” [Kimberly Neuendorf, The Content Analysis Guidebook, Sage Publications] At Pew Research Center, much of our content analysis has been used to study news reporting and social media, but the methodology can be applied to many different forms of communication, from transcripts of speeches to Twitter feeds. We have measured the “news agenda” (the topics being covered by the news media), the framing of conversations and many other characteristics of messages.
At Pew Research, we began our content analysis work under the guidance of some of the nation’s top content analysis methodologists and with a large team of human coders. We have always followed rigorous standards of validity and replicability by explaining our methods and conducting intercoder testing. In recent years, we have begun experimenting with the potential for computer coding. The center’s use of these new computer algorithms creates new opportunities and challenges for our work. In the following sections, we lay out some of the key methods underlying our content analysis and coding work.