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| Phân tích trích dẫn có sự hỗ trợ của Bibliometrix× | Phân tích đồng trích dẫn (Co-Citation Analysis)× | |
|---|---|---|
| Lĩnh vực≠ | Trắc lượng khoa học | Trắc lượng thư mục |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 2017 (bibliometrix package); citation analysis since 1955 | 1973 |
| Người khởi xướng≠ | Massimo Aria & Corrado Cuccurullo (bibliometrix R package); citation analysis concepts from Eugene Garfield (1955) | Henry Small |
| Loại≠ | Quantitative bibliometric pipeline | Method |
| Công trình gốc≠ | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. DOI ↗ | Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265–269. DOI ↗ |
| Tên gọi khác | bibliometrix citation analysis, R-based citation analysis, bibliometrix CA, citation analysis with bibliometrix | co-citation mapping, historiograph, direct citation, citation pair analysis |
| Liên quan≠ | 6 | 5 |
| Tóm tắt≠ | Bibliometrix-assisted citation analysis uses the bibliometrix R package to systematically retrieve, clean, and analyze citation data exported from major databases such as Web of Science and Scopus. By automating reference parsing, frequency counting, and network construction, it enables researchers to identify the most-cited works, map intellectual influence, and trace the evolution of scholarly fields at a scale that manual analysis cannot match. | Co-citation analysis is a method that identifies the intellectual structure of a research domain by examining how frequently pairs of documents are cited together in other publications. When two papers are frequently cited together in the literature, they are considered co-cited, indicating they are conceptually related or influential within the same research community. Developed by Henry Small in 1973, co-citation analysis maps the 'invisible colleges' of science—networks of researchers working on related problems—and reveals how knowledge domains evolve over time. |
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