Mining author relationship in scholarly networks based on tripartite citation analysis

Abstract

Following scholars in Scientometrics as examples, we develop five author relationship networks, namely, co-authorship, author co-citation (AC), author bibliographic coupling (ABC), author direct citation (ADC), and author keyword coupling (AKC). The time frame of data sets is divided into two periods: before 2011 (i.e., T1) and after 2011 (i.e., T2). Through quadratic assignment procedure analysis, we found that some authors have ABC or AC relationships (i.e., potential communication relationship, PCR) but do not have actual collaborations or direct citations (i.e., actual communication relationship, ACR) among them. In addition, we noticed that PCR and AKC are highly correlated and that the old PCR and the new ACR are correlated and consistent. Such facts indicate that PCR tends to produce academic exchanges based on similar themes, and ABC bears more advantages in predicting potential relations. Based on tripartite citation analysis, including AC, ABC, and ADC, we also present an author-relation mining process. Such process can be used to detect deep and potential author relationships. We analyze the prediction capacity by comparing between the T1 and T2 periods, which demonstrate that relation mining can be complementary in identifying authors based on similar themes and discovering more potential collaborations and academic communities.

The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis

“…Co-citation analysis is often used to evaluate the relevance of articles or authors. In addition, it can be an indicator to appraise the academic influence of authors ( 72 , 73 ). As shown in Supplementary Table S1 , the most cited article in this study was Tang et al.…”

A state-of-the-art appraisal of bankruptcy prediction models focussing on the field’s core authors: 2010–2022

“…The designation “core” stands for the relation to the field of study. Initially, Wang, Qiu, & Yu (2012) claimed that there was no report on any standard for identifying core authors in a scientific field, but in a later scientometric article (Wang et al. , 2017), they adopted criteria of inclusion of authors who published five or more papers and received ten or more citations.…”

“…, 2018). Therefore, we adopted criteria based on a dedication to the field of study and audience response, as cited by Wang et al. (2017).…”

“…We find a similar approach of citing and authorship analysis in other scientometric studies, for example, literature co-citation and the innovation path analysis of a research field (Gu et al, 2017), number of articles and network density analysis (Castro & Parreiras, 2018), or co-authorship frequency (Ouyang et al, 2018). Therefore, we adopted criteria based on a dedication to the field of study and audience response, as cited by Wang et al (2017). We applied the criteria after the screening phase and content eligibility criteria analysis.…”

“…We focused on core authors to find the most recognized and dedicated authors in the area of bankruptcy prediction. Although some studies connect a core status only to the citation status, scientometric studies suggest another approach combining various criteria (Gu, Li, Li, & Liang, 2017;Ouyang et al, 2018;Wang, Wang, & Yang, 2017). Hence, we adopted a combination of impact reflection techniques, wherein the minimum required number of articles in the research accompanied citations and dedication to the research.…”