Identifying Media Frames and Frame Dynamics Within and Across Policy Issues

Framing is a central concept in political communication and a powerful political tool. Understanding what frames are used to define specific issues and also what general patterns are evidenced by the evolution of frames over time is hugely important. It is also a serious challenge, thanks to the volume of text data, the dynamic nature of language, and the variance in applicable frames across issues (e.g., the ‘innocence’ frame of the death penalty debate is not used in discussing smoking bans). We describe a project that advances framing research methodology in two ways. First, we are developing a unified coding scheme for content analysis across issues, whereby issue-specific frames (e.g., innocence) are nested within high-level dimensions (or frame types) that cross-cut issues (e.g., fairness); we are validating this coding scheme by applying it to news coverage of immigration, same-sex marriage, and smoking/tobacco in the United States over the course of the past twenty-three years. Second, we are developing methods for semi-automated and automated frame discovery aimed at both replicating manual coding and isolating patterns of frame evolution that might not be readily visible to human inspection. Our goal is to employ strategies heavily informed by existing work in natural language processing, but tailored to the specific needs and professional sensibilities of political communications scholars.