Using author tri-citation analysis to map knowledge domains in knowledge representations

Abstract

Purpose Previous commonly used author co-citation analysis (ACA) methods have limited the ability to deal with accidental co-citation in constructing a raw co-citation matrix. Therefore, the purpose of this paper is to propose a new method, called author tri-citation analysis (ATA), to better map knowledge domains and depict scientific intellectual structures. Design/methodology/approach Different from the previous method of using ACA that captures author co-citation relationships, the ATA method seeks tri-citation relationships among authors. Compared with ACA, ATA can ignore some accidental co-citation relationships between authors and can improve the accuracy of mapping knowledge domains. Findings Although ATA does not mine more sub-fields than ACA does, the results of the empirical studies show that ATA, the newly proposed method, performs better in knowledge domain maps based on publications in the field of computer science. Research limitations/implications The definition of ATA in this article is simple and still insufficiently informative. Many other pieces of information can be involved; for example, all authors’ information, authors’ sequence in the author list, reference published time and similar. These can be enhanced in future studies. Practical implications This research will enrich the methods of mapping knowledge domains due to its new perspective. Social implications Knowledge domain mapping is important to understand a discipline, and this research provides more potential methods for this, which benefits the performance of the maps. Originality/value ATA can provide a methodological awareness for mapping knowledge domains. This value lies in not only a tri-citation perspective, but also author bibliographic tripling and author tri-operation perspectives (“tri-” perspectives).