In order to investigate the impact of research topic selection time on output performance of scientific collaborations, the aim of this study is to develop a differential analysis framework of scientific collaboration performance at different stages of entity popularity. The framework consists of three main sections: (1) data acquisition and processing; (2) stage division of entity popularity; (3) differential analysis on performance of scientific collaborations at different stages of entities popularity. Our findings show that the popularity stage that research topics are going through can play a role in the collaboration output performance.
Computing in government • Information systems → Information
retrieval
The ultimate success of scientific collaborations depends on a
number of factors, among which the importance of identifying
promising research topics as a key success factor should not be
underestimated [
The framework of differential analysis on performance of scientific collaborations in different stages of entity popularity is shown in Figure 1. In Figure 1, three functional modules of the analysis framework and concrete work done in modules are as follow.
Data acquisition and processing. By using BERT [
Stage division of entity popularity. After the normalization
processing of entity frequency, we deal with the division of entity
popularity stages based on the model tree proposed by Ma [
Copyright 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Differential analysis on performance of scientific collaborations in various stages of entity popularity. Through comparing statistics on the number of published periodical articles and citations of teams of each scientific collaboration in the ascending and descending stages, the impact of entity popularity stage that a collaboration is going through when selecting a research topic on its performance and the mechanism behind is discussed. For scientific collaborations studying entities in various popularity stages, we recognize authors of the same article as a research team.
Teams in which the number of authors is less than three or over 10, and groups in which ages of authors are all over 45 are ruled out.
As long as the target entities appear in the title of abstract of an
article, we consider the team has studied the entities. The index of
normalized citations [
SC=(PC-AC)/SDC #(1) where, PC denotes the absolute citation of a certain article, AC denotes the average absolute citation of all articles in the publication year of the article, SDC denotes the standard deviation of the absolute citation of all articles in the same year, and SC denotes the normalized citation (SC).
Figure 2 shows the evolution of the number of articles of teams in the ascending and descending stages by year. After the 21st century, the number of teams conducting research in the ascending stage of entities popularity has experienced rapid growth while the number of teams on the other side shows a slightly declining trend. As shown in Figure 3, either the overall average normalized citations or the annual average normalized citations of teams in the ascending stage remains significantly higher than that of teams in the descending stage. For research outputs of teams in the ascending stage, the earlier the published year, the more normalized citations compared to teams in the descending stage. It illustrates that team research in the ascending stage is more likely to have a far-reaching academic influence than that in the descending stage.
The study proposes a preliminary research design, applying the idea of entitymetrics to team research performance and engaged in preliminary differential analysis.
Results show that: The popularity stage that research topics are going through can play a role in the research performance of scientific collaborations Compared with the descending stage, the ascending stage puts more positive impacts on collaboration research performance. For different scientific collaboration modes, the study can be used as a reference in choosing research topics. For instance, when selecting topics for research, authors can implement the strategy of choosing a topic the popularity of which is in its ascending stage as a way to moderate the negative influence of descending stage on collaborative performance.
In the future, differences in other aspects such as personnel composition of a team will be considered in the study. Furthermore, an important question waiting to be answered is how sustentation funding, one of the most important external resources to encourage team research, distributes in the two types of teams? Therefore, we will further study other aspects of characteristics of teams at different stages of topic selection in the future.
This work is supported by National Social Science Fund of China [18BTQ076].