방법 비교
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| bibliometrix 기반 매핑 검토× | 매핑 검토× | |
|---|---|---|
| 분야 | 과학계량학 | 과학계량학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2017 (bibliometrix tool); mapping review approach formalised c. 2010s | Late 1990s–2000s; major methodological formalization ~2010s |
| 창시자≠ | Aria & Cuccurullo (bibliometrix, 2017); mapping review methodology developed in evidence synthesis community (~2000s) | Buckland & Gann (1998); formalized by systematic review community (Campbell Collaboration, Collaboration for Environmental Evidence) |
| 유형≠ | Tool-assisted evidence mapping review | Systematic evidence mapping methodology |
| 원전≠ | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. DOI ↗ | James, K. L., Randall, N. P., & Haddaway, N. R. (2016). A methodology for systematic mapping in environmental sciences. Environmental Evidence, 5(1), 7. DOI ↗ |
| 별칭 | bibliometrix mapping review, R-bibliometrix evidence map, bibliometric-assisted systematic map, bibliometrix evidence synthesis map | evidence map, systematic map, research map, literature map |
| 관련≠ | 5 | 6 |
| 요약≠ | A bibliometrix-assisted mapping review combines the structured scope-and-search logic of an evidence mapping review with the analytical power of the bibliometrix R package. Instead of manually categorising studies, the researcher leverages bibliometrix functions — keyword co-occurrence networks, thematic clustering, and yearly trend analysis — to chart the landscape of a research field systematically and at scale, producing an interactive, reproducible evidence map. | A mapping review (also called a systematic map or evidence map) is a form of systematic review that aims to chart the extent, range, and nature of evidence on a broad topic rather than synthesize findings into a single pooled answer. It categorizes studies by key dimensions — such as intervention type, population, outcome, and study design — and presents the resulting landscape visually and tabularly so that researchers and practitioners can identify clusters of evidence, knowledge gaps, and priorities for future primary research or deeper synthesis. |
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