Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise Cienciométrica em Fatias Temporais× | Science Mapping× | |
|---|---|---|
| Área≠ | Cientometria | Bibliometria |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 1980s–1990s | 2000s |
| Autor original≠ | Derived from scientometrics tradition; temporal slicing formalized in longitudinal bibliometric studies from the 1980s onward | Katy Börner, Chaomei Chen, and others |
| Tipo≠ | Quantitative longitudinal analysis | Method |
| Fonte seminal≠ | 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 ↗ |
| Outros nomes≠ | temporal scientometrics, period-based scientometric analysis, time-window scientometrics, longitudinal scientometric analysis | knowledge mapping, domain mapping, research landscape visualization |
| Relacionados≠ | 6 | 5 |
| Resumo≠ | 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. |
| ScholarGateConjunto de dados ↗ |
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