Fuzzy C-Means Clustering as a Discourse Analysis Method (Case Study: Institutional Interactions of Science and Technology Policy in Iran)
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...
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| Format: | Article |
| Language: | fas |
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پژوهشگاه حوزه و دانشگاه
2021-06-01
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| Series: | روش شناسی علوم انسانی |
| Subjects: | |
| Online Access: | https://method.rihu.ac.ir/article_1821_85ea7688f3bf4bf9e50e0a4554afcbcf.pdf |
| _version_ | 1797303892716814336 |
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| author | esmaeel kalantari gholamali montazer Sepehr Ghazinoory |
| author_facet | esmaeel kalantari gholamali montazer Sepehr Ghazinoory |
| author_sort | esmaeel kalantari |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T00:00:10Z |
| format | Article |
| id | doaj.art-d18c6a8be80b4c4f8868c3305fe92ce1 |
| institution | Directory Open Access Journal |
| issn | 1608-7070 2588-5774 |
| language | fas |
| last_indexed | 2024-03-08T00:00:10Z |
| publishDate | 2021-06-01 |
| publisher | پژوهشگاه حوزه و دانشگاه |
| record_format | Article |
| series | روش شناسی علوم انسانی |
| spelling | doaj.art-d18c6a8be80b4c4f8868c3305fe92ce12024-02-18T04:56:37Zfasپژوهشگاه حوزه و دانشگاهروش شناسی علوم انسانی1608-70702588-57742021-06-0127107153310.30471/mssh.2020.6861.20931821Fuzzy C-Means Clustering as a Discourse Analysis Method (Case Study: Institutional Interactions of Science and Technology Policy in Iran)esmaeel kalantari0gholamali montazer1Sepehr Ghazinoory2Tarbiat Modares UniversityTarbiat Modares UniversityTarbiat Modares UniversityIn 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.https://method.rihu.ac.ir/article_1821_85ea7688f3bf4bf9e50e0a4554afcbcf.pdffuzzy c-means clusteringdiscourse analysismethodologyinstitutional interactionsscience and technology policyiran |
| spellingShingle | esmaeel kalantari gholamali montazer Sepehr Ghazinoory Fuzzy C-Means Clustering as a Discourse Analysis Method (Case Study: Institutional Interactions of Science and Technology Policy in Iran) روش شناسی علوم انسانی fuzzy c-means clustering discourse analysis methodology institutional interactions science and technology policy iran |
| title | Fuzzy C-Means Clustering as a Discourse Analysis Method (Case Study: Institutional Interactions of Science and Technology Policy in Iran) |
| title_full | Fuzzy C-Means Clustering as a Discourse Analysis Method (Case Study: Institutional Interactions of Science and Technology Policy in Iran) |
| title_fullStr | Fuzzy C-Means Clustering as a Discourse Analysis Method (Case Study: Institutional Interactions of Science and Technology Policy in Iran) |
| title_full_unstemmed | Fuzzy C-Means Clustering as a Discourse Analysis Method (Case Study: Institutional Interactions of Science and Technology Policy in Iran) |
| title_short | Fuzzy C-Means Clustering as a Discourse Analysis Method (Case Study: Institutional Interactions of Science and Technology Policy in Iran) |
| title_sort | fuzzy c means clustering as a discourse analysis method case study institutional interactions of science and technology policy in iran |
| topic | fuzzy c-means clustering discourse analysis methodology institutional interactions science and technology policy iran |
| url | https://method.rihu.ac.ir/article_1821_85ea7688f3bf4bf9e50e0a4554afcbcf.pdf |
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