Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Обзор на основе PRISMA с использованием библиометрического анализа× | Библиометрический анализ с использованием bibliometrix× | |
|---|---|---|
| Область | Наукометрия | Наукометрия |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2017 (bibliometrix); 2009/2021 (PRISMA) | 2017 |
| Автор метода≠ | Aria & Cuccurullo (bibliometrix package); Moher et al. / Page et al. (PRISMA statement) | Massimo Aria and Corrado Cuccurullo (bibliometrix R package) |
| Тип≠ | Software-assisted systematic review workflow | Quantitative review method with software toolkit |
| Основополагающий источник | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. DOI ↗ | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. DOI ↗ |
| Другие названия | bibliometrix PRISMA review, R-bibliometrix systematic review, bibliometrix-enhanced evidence synthesis, bibliometrix-supported PRISMA review | bibliometrix bibliometric analysis, R-based bibliometric analysis, bibliometrix workflow, bibliometrix package analysis |
| Связанные≠ | 5 | 6 |
| Сводка≠ | A bibliometrix-assisted PRISMA-based review combines the structured, transparent reporting framework of PRISMA with the quantitative science-mapping capabilities of the bibliometrix R package. The approach embeds bibliometric analyses — such as citation analysis, co-authorship mapping, and keyword co-occurrence — into the evidence-synthesis steps of a PRISMA-guided systematic review, enabling both rigorous literature screening and macro-level visualization of the intellectual landscape. | bibliometrix-assisted bibliometric analysis is a structured quantitative approach to mapping a scientific field using the bibliometrix R package. Developed by Aria and Cuccurullo (2017), it provides an integrated environment for importing bibliographic records from Scopus or Web of Science, computing performance indicators, building co-authorship and citation networks, and generating thematic maps — all within a reproducible R or Shiny workflow. |
| ScholarGateНабор данных ↗ |
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