Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uchambuzi wa Usanifu wa Jarida (Journal Co-Citation Analysis)× | Ramani ya Kisayansi× | |
|---|---|---|
| Nyanja | Bibliometriki | Bibliometriki |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1981 | 2000s |
| Mwanzilishi≠ | Henry Small, Henry White, and others | Katy Börner, Chaomei Chen, and others |
| Aina | Method | Method |
| Chanzo asilia≠ | White, H. D., & Griffith, B. C. (1981). Author co-citation: A literature measure of intellectual structure. Journal of the American Society for Information Science, 32(3), 163–171. DOI ↗ | Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255. DOI ↗ |
| Majina mbadala | journal citation mapping, journal network analysis, cited source co-citation | knowledge mapping, domain mapping, research landscape visualization |
| Zinazohusiana≠ | 4 | 5 |
| Muhtasari≠ | Journal co-citation analysis is a bibliometric method that maps the intellectual structure of a research field by analyzing how frequently pairs of journals are cited together in the same papers. Two journals are co-cited when papers cite both journals, indicating that the journals are perceived as intellectually related by the citing authors. This extension of paper-level co-citation analysis to the journal level reveals the topological structure of journal relationships, disciplinary boundaries, and the role of different journals within research communities. | Science mapping is a bibliometric visualization method that creates visual representations of research domains, showing the structure, development, and relationships of scientific fields. Using bibliographic data (citations, keywords, authors, journals), science mapping algorithms generate network diagrams where nodes represent documents, concepts, or authors and edges represent relationships (citation, collaboration, semantic similarity). The resulting maps make invisible intellectual structures visible, enabling researchers to understand field topology, identify emerging areas, and navigate disciplinary landscapes. Pioneered by Börner, Chen, and Boyack in the 2000s, science mapping has become a standard tool in research evaluation and strategic planning. |
| ScholarGateSeti ya data ↗ |
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