Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Аналіз цитувань за допомогою бібліометрикс× | Систематичний огляд літератури× | |
|---|---|---|
| Галузь | Наукометрія | Наукометрія |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 2017 (bibliometrix package); citation analysis since 1955 | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Автор методу≠ | Massimo Aria & Corrado Cuccurullo (bibliometrix R package); citation analysis concepts from Eugene Garfield (1955) | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Тип≠ | Quantitative bibliometric pipeline | Evidence synthesis methodology |
| Основоположне джерело≠ | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. DOI ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| Інші назви | bibliometrix citation analysis, R-based citation analysis, bibliometrix CA, citation analysis with bibliometrix | SLR, systematic review, evidence synthesis review, structured literature review |
| Пов'язані≠ | 6 | 5 |
| Підсумок≠ | Bibliometrix-assisted citation analysis uses the bibliometrix R package to systematically retrieve, clean, and analyze citation data exported from major databases such as Web of Science and Scopus. By automating reference parsing, frequency counting, and network construction, it enables researchers to identify the most-cited works, map intellectual influence, and trace the evolution of scholarly fields at a scale that manual analysis cannot match. | A systematic literature review (SLR) is a structured, reproducible method for identifying, appraising, and synthesizing all relevant studies on a research question. Unlike a narrative review, it follows an explicit, pre-specified protocol — from database search strings through inclusion criteria to data extraction — so that the process is transparent, auditable, and replicable by other researchers. It is widely used in medicine, education, software engineering, and the social sciences to produce the most comprehensive possible evidence base on a topic. |
| ScholarGateНабір даних ↗ |
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