So sánh phương pháp

	Phân tích đồng trích dẫn có hỗ trợ bibliometrix	Phân tích đồng trích dẫn (Co-Citation Analysis)
Lĩnh vực	Trắc lượng khoa học	Trắc lượng thư mục
Họ	Process / pipeline	Process / pipeline
Năm ra đời	2017 (bibliometrix implementation); 1973 (co-citation concept)	1973
Người khởi xướng	Co-citation: Henry Small (1973); bibliometrix package: Massimo Aria & Corrado Cuccurullo (2017)	Henry Small
Loại	Computational scientometric pipeline	Method
Công trình gốc	Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975.	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.
Tên gọi khác	R bibliometrix co-citation, bibliometrix CCA, co-citation network analysis with bibliometrix, bibliometrix cocitation mapping	co-citation mapping, historiograph, direct citation, citation pair analysis
Liên quan	6	5
Tóm tắt	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.	Co-citation analysis is a method that identifies the intellectual structure of a research domain by examining how frequently pairs of documents are cited together in other publications. When two papers are frequently cited together in the literature, they are considered co-cited, indicating they are conceptually related or influential within the same research community. Developed by Henry Small in 1973, co-citation analysis maps the 'invisible colleges' of science—networks of researchers working on related problems—and reveals how knowledge domains evolve over time.