Bridging qualitative and quantitative methods for classifying policy actors into policy discourse communities: thematic analysis and formal concept analysis approaches

Policy decision process is usually depicted as a neutral and technical process in which problem solving capacity of a policy decision determines the validity of its effectiveness. However, socio-political space is fragmented and policy making process reflects the conflicts between different socio-political actors. Empirical detection of policy networks is a problematic issue since world views reflecting policy beliefs can best be elicited in unstructured narrative forms which do not easily lend themselves to a systematic and objective classification of the narrating actors. Thus, the data for such research is usually collected through structured interviews which provide a solid basis for quantitative classification techniques such as cluster analysis. However, structured interviews are prone to imposing researcher's perspective to the data rather than reflecting the world views of the policy actors. The aim of this paper is to offer a systematic way of classifying policy actors into policy communities according to the data collected through unstructured policy narratives. For this purpose the paper proposes a method that bridges qualitative thematic analysis with quantitative formal concept analysis.