ScholarGate
Msaidizi

Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Uchambuzi wa Kisayansi wa Vipande vya Wakati×Uchanganuzi wa Mageukio ya Kimaudhui×
NyanjaSaintometrikiSaintometriki
FamiliaProcess / pipelineProcess / pipeline
Mwaka wa asili1980s–1990s2011
MwanzilishiDerived from scientometrics tradition; temporal slicing formalized in longitudinal bibliometric studies from the 1980s onwardManuel J. Cobo and colleagues (University of Granada)
AinaQuantitative longitudinal analysisQuantitative bibliometric technique
Chanzo asiliaSmall, H. (1999). Visualizing science by citation mapping. Journal of the American Society for Information Science, 50(9), 799-813. link ↗Cobo, M. J., Lopez-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382–1402. DOI ↗
Majina mbadalatemporal scientometrics, period-based scientometric analysis, time-window scientometrics, longitudinal scientometric analysisTEA, thematic development analysis, temporal thematic mapping, longitudinal theme analysis
Zinazohusiana66
MuhtasariTime-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.Thematic evolution analysis is a bibliometric technique that divides a body of literature into consecutive time periods and tracks how research themes emerge, consolidate, split, merge, or disappear across those periods. By combining co-word analysis, clustering, and strategic diagrams for each time slice, it produces a dynamic picture of a field's intellectual development rather than a static snapshot.
ScholarGateSeti ya data
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

Nenda kwenye utafutaji Pakua slaidi

ScholarGateLinganisha mbinu: Time-sliced Scientometric Analysis · Thematic Evolution Analysis. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare