Fuzzy C-Means Clustering as a Discourse Analysis Method (Case Study: Institutional Interactions of Science and Technology Policy in Iran)

Abstract

In this paper, an attempt has been made to develop a qualitative method of discourse analysis in a mixed (qualitative-quantitative) method by using the quantitative method of fuzzy c-means clustering. For this purpose, the institutional interactions of science and technology policy in Iran have been studied as a case study. Therefore, according to the "exploratory sequential mixed method", first using the fuzzy c-means clustering method and the questionnaire tool, the discourses of experts on the subject are identified and then using the Laclau and Mouffe discourse analysis method and interview tools to explain the nodal points, moments and articulations. Thus, "collaborative discourse" around the nodal point of "integrated policy making" and "independent discourse" around the nodal point of "government policy making" were identified. The most important result of this research is the development of discourse analysis method from qualitative paradigm to mixed paradigm and of course increasing the validity of research findings. In addition, this innovation is in line with the main stream in methodology and, due to the use of fuzzy logic, is very similar to the ambiguous and complex concepts of social sciences.

Keywords

• fuzzy c-means clustering
• discourse analysis
• methodology
• institutional interactions
• science and technology policy
• iran