Exploring all-author tripartite citation networks: A case study of gene editing

An exploratory study of the all-author bibliographic coupling analysis: Taking scientometrics for example

All-author bibliographic coupling analyses (AABCA) take all authors of the article into account when constructing author coupling relationships. Taking scientometrics as an example, this article takes the papers from 2010 to 2019 as data sample and divides them into two periods (limited to 5 years) to discuss the performance of AABCA in discovering potential academic communities and intellectual structure of this discipline. It is found that when all authors of the paper are considered, the relationship between the bibliographic coupling authors presents a certain regularity and the bibliographic coupling is likely to be passed between different pairs of authors. With the transitivity of the coupling relationship, AABCA can effectively identify and discover the potential academic groups of this discipline, and more fully reflect the degree of cooperation among authors. AABCA is an effective method to reveal the intellectual structure in the field of scientometrics, and it is easier to find some small research topics with weak correlation. In addition, AABCA is also an ideal way to explore the author’s research interests over time.

Bibliometric analysis for talent identification by the subject–author–citation three-dimensional evaluation model in the discipline of physical education

Purpose

In order to solve the current imbalance of academic resources within the discipline, this article builds a three-dimensional talent evaluation model based on the topic–author–citation based on the z index and proposes the ZAS index to evaluate scholars on different research topics within the discipline.

Design/methodology/approach

Based on the sample data of the CSSCI journals in the discipline of physical education in the past five years, the keywords were classified into 13 categories of research topics including female sports. The ZAS index of scholars on topic of female sports and so on was calculated, and quantitative indexes such as h index p index and z index were calculated. Comparative analysis of the evaluation effect was performed.

Findings

It is found that compared with the h index and p index, the z index achieves a better balance between the quantity, quality and citation distribution of scholars' results and effectively recognizes that the citation quality is higher and the number of citations of each paper is more balanced. In addition, compared to the z index, this article is based on a ZAS index model with an improved three-dimensional topic–author–citation relationship in research fields such as female sports.

Originality/value

It can identify some outstanding scholars who are engaged in small-scale or emerging topic research such as female sports and are excellent in different research areas. Talents create an objective and fair evaluation environment. At the same time, the ranking ability of ZAS indicators in the evaluation of talents is the strongest, and it is expected to be used in practical evaluations.

Distribution of Node Characteristics in Evolving Tripartite Network

Many real-world networks have a natural tripartite structure. Investigating the structure and the behavior of actors in these networks is useful to gain a deeper understanding of their behavior and dynamics. In our paper, we describe an evolving tripartite network using a network model with preferential growth mechanisms and different rules for changing the strength of nodes and the weights of edges. We analyze the characteristics of the strength distribution and behavior of selected nodes and selected actors in this tripartite network. The distributions of these analyzed characteristics follow the power-law under different modeled conditions. Performed simulations have confirmed all these results. Despite its simplicity, the model expresses well the basic properties of the modeled network. It can provide further insights into the behavior of systems with more complex behaviors, such as the multi-actor e-commerce system that we have used as a real basis for the validation of our model.