Discourse Network Analysis is a methodological toolbox for measuring and analysing policy debates and their development over time. The software Discourse Network Analyzer (DNA) allows researchers to manually code actors’ opinions about policies in text data. Similar to other qualitative content analysis tools, the user annotates statements of political actors about their preferred or rejected concepts, policy instruments, frames, or beliefs. Text sources can include newspaper articles, parliamentary testimony, press agencies, or social media. DNA then exports various kinds of network data based on the user’s coding.
These networks capture relationships between political actors based on their congruence or conflict around concepts. Aggregated networks help identify discourse coalitions, advocacy coalitions, brokers, opinion leaders, central actors and concepts, dimensionality of discourse, frames composed of different concepts, and the evolution of debates over time. Researchers can apply ideological scaling techniques to measure actors’ ideal points or model contributions to the debate using statistical methods.
The course explores connections between discourse network analysis and policy process theories, covering best practices for coding statements in text data. It introduces statistical and exploratory methods for network analysis and dedicates about half the time to software implementations, including DNA, R, and visone, and a practical example.
- Instructor: Philip Leifeld