เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| การวิเคราะห์บรรณมิติแบบแบ่งช่วงเวลา× | การสร้างแผนที่วิทยาศาสตร์× | |
|---|---|---|
| สาขาวิชา≠ | วิทยาศาสตรมิติ | บรรณมิติ |
| ตระกูล | Process / pipeline | Process / pipeline |
| ปีกำเนิด≠ | 1980s–1990s | 2000s |
| ผู้ริเริ่ม≠ | Derived from scientometrics tradition; temporal slicing formalized in longitudinal bibliometric studies from the 1980s onward | Katy Börner, Chaomei Chen, and others |
| ประเภท≠ | Quantitative longitudinal analysis | Method |
| แหล่งต้นตำรับ≠ | Small, H. (1999). Visualizing science by citation mapping. Journal of the American Society for Information Science, 50(9), 799-813. link ↗ | Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255. DOI ↗ |
| ชื่อเรียกอื่น≠ | temporal scientometrics, period-based scientometric analysis, time-window scientometrics, longitudinal scientometric analysis | knowledge mapping, domain mapping, research landscape visualization |
| ที่เกี่ยวข้อง≠ | 6 | 5 |
| สรุป≠ | Time-sliced scientometric analysis divides a bibliographic corpus into discrete temporal windows — commonly five- or ten-year periods — and applies standard scientometric indicators (publication counts, citation rates, h-index, collaboration networks, keyword co-occurrence) within each slice. By comparing results across slices, researchers can reconstruct how a scientific field has grown, shifted focus, formed new collaborations, or declined in influence over time. The approach combines the rigor of quantitative scientometrics with an explicit longitudinal dimension. | 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. |
| ScholarGateชุดข้อมูล ↗ |
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