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タイムスライス型テーマ進化分析×共起語分析×
分野科学計量学科学計量学
系統Process / pipelineProcess / pipeline
提唱年2011–20121983
提唱者Cobo, López-Herrera, Herrera-Viedma & HerreraMichel Callon, Jean-Pierre Courtial, and colleagues
種類Longitudinal bibliometric analysisScientometric network analysis technique
原典Cobo, M. J., López-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 ↗Callon, M., Courtial, J. P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social Science Information, 22(2), 191–235. DOI ↗
別名longitudinal thematic mapping, temporal thematic evolution, time-period thematic analysis, diachronic science mappingkeyword co-occurrence analysis, co-word mapping, keyword co-word network, CWA
関連66
概要Time-sliced thematic evolution analysis is a bibliometric method that divides a corpus of publications into consecutive time windows and tracks how research themes emerge, consolidate, split, merge, or disappear across those periods. By applying co-word analysis and strategic-diagram mapping within each slice and then linking themes across slices, it reveals the intellectual trajectory of a research field over time.Co-word analysis is a scientometric technique that quantifies how often pairs of keywords, subject terms, or title words appear together across a corpus of publications. By treating simultaneous occurrence as a proxy for conceptual relatedness, it constructs networks and clusters that reveal the intellectual structure, dominant themes, and emerging sub-fields of a research domain.
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ScholarGate手法を比較: Time-sliced Thematic Evolution Analysis · Co-word Analysis. 2026-06-18に以下より取得 https://scholargate.app/ja/compare