MACA: a modified author co-citation analysis method combined with general descriptive metadata of citations

Yi Bu, Tian-yi Liu and Win-bin Huang ()
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Yi Bu: Peking University
Tian-yi Liu: Peking University
Win-bin Huang: Peking University

Scientometrics, 2016, vol. 108, issue 1, No 7, 143-166

Abstract: Abstract Author co-citation analysis (ACA) is a well-known and frequently-used method to exhibit the academic researchers and the professional field sketch according to co-citation relationships between authors in an article set. However, visualizing subtle examination is limited because only author co-citation information is required in ACA. The proposed method, called modified author co-citation analysis (MACA), exploits author co-citation relationship, citations published time, citations published carriers, and citations keywords, to construct MACA-based co-citation matrices. According to the results of our experiments: (1) MACA shows a good clustering result with more delicacy and more clearness; (2) more information involved in co-citation analysis performs good visual acuity; (3) in visualization of co-citation network produced by MACA, the points in different categories have far more distance, and the points indicating authors in the same category are closer together. As a result, the proposed MACA is found that more detailed and subtle information of a knowledge domain analyzed can be obtained, compared to ACA.

Keywords: Author co-citation analysis; Co-citation analysis; Citation analysis; Bibliometrics; 68T30 (search for similar items in EconPapers)
JEL-codes: D83 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (8)

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DOI: 10.1007/s11192-016-1959-5

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