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Discourse Network Analysis is a methodological toolbox for measuring and analyzing 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.
In a way 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. Useful text sources can be newspaper articles, parliamentary testimony, press agencies, or social media. DNA then allows the researcher to export various kinds of network data based on what the user coded.
The network data capture the relationships between political actors based on their congruence or conflict around concepts. As these relationships are aggregated into a network, the user can identify discourse coalitions or advocacy coalitions in these networks, identify brokers, opinion leaders, and central actors and concepts, examine the dimensionality of the discourse, find frames composed of different concepts through co-agreement by multiple actors, track the evolution of the policy debate over time (for example before policy change occurs), apply ideological scaling techniques to measure actors’ ideological ideal points relative to each other, or model the contributions by actors to the debate using statistical techniques.
This summer course explores the connections between discourse network analysis and a number of policy process theories. We will cover best practices for coding statements in text data.
