方法对比
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| bibliometrix辅助的共被引分析× | 基于网络的共被引分析× | |
|---|---|---|
| 领域 | 科学计量学 | 科学计量学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 2017 (bibliometrix implementation); 1973 (co-citation concept) | 1973 (co-citation); network-analytic extension widely adopted 2000s–2010s |
| 提出者≠ | Co-citation: Henry Small (1973); bibliometrix package: Massimo Aria & Corrado Cuccurullo (2017) | Henry Small (co-citation foundation); network visualization extended by Chaomei Chen and others |
| 类型≠ | Computational scientometric pipeline | Bibliometric network analysis |
| 开创性文献≠ | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. DOI ↗ | Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265–269. DOI ↗ |
| 别名 | R bibliometrix co-citation, bibliometrix CCA, co-citation network analysis with bibliometrix, bibliometrix cocitation mapping | co-citation network analysis, bibliometric network co-citation, co-citation mapping, CCA network approach |
| 相关 | 6 | 6 |
| 摘要≠ | bibliometrix-assisted co-citation analysis combines Henry Small's co-citation measure with the open-source R package bibliometrix to map the intellectual structure of a research field. When two documents are frequently cited together by third papers, they are considered intellectually linked; the bibliometrix package automates construction of the co-citation matrix, similarity normalization, community detection, and network visualization, turning raw bibliographic exports into interpretable science maps. | Network-based co-citation analysis is a bibliometric technique that measures how often pairs of documents are cited together by later works, then models those relationships as a weighted network. Nodes represent documents (or authors or journals), edges represent co-citation frequency, and network algorithms identify clusters of intellectually related literature. It is widely used in systematic and scoping reviews to map the intellectual structure of a research field. |
| ScholarGate数据集 ↗ |
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