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| 文献耦合分析× | 关键词共现分析× | |
|---|---|---|
| 领域 | 文献计量学 | 文献计量学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1963 | 2000s |
| 提出者≠ | Melvin M. Kessler | Bibliometric research community |
| 类型 | Method | Method |
| 开创性文献≠ | Kessler, M. M. (1963). Bibliographic coupling between scientific papers. American Documentation, 14(3), 123–131. DOI ↗ | Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the fuzzy sets theory field. Journal of Informetrics, 5(1), 146–166. DOI ↗ |
| 别名≠ | document coupling, bibliographic similarity | term co-occurrence, keyword network analysis, thematic analysis, term clustering |
| 相关≠ | 5 | 4 |
| 摘要≠ | Bibliographic coupling is a method that identifies intellectual relationships between documents by measuring their shared references. Two papers are considered 'coupled' when they cite the same sources, indicating they address related research questions or draw from the same conceptual foundations. Introduced by Kessler in 1963, this approach enables researchers to map knowledge domains and discover thematically similar publications without relying on subject cataloging or keywords. | Keyword co-occurrence analysis is a text mining and bibliometric method that identifies research themes and their relationships by analyzing how frequently terms or keywords appear together in abstracts, titles, or indexed keywords of scientific publications. When two keywords appear together frequently, they are considered co-occurring, indicating a shared thematic or conceptual relationship. This method rapidly reveals the topical structure of a research field without relying on formal classifications, making it particularly useful for detecting emerging research areas and understanding disciplinary boundaries. |
| ScholarGate数据集 ↗ |
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