Research Teams’Evolution and Leaders’Influence

[Objective] This paper uses the stem cell field as an empirical example to investigate the evolution of research teams, the changes in author influence, and their relationships. [Methods] We employed the Leiden algorithm to extract community structures in the collaboration network. Then, we determined the leaders based on the influence variance. We utilized the Pearson correlation coefficient to explore the relationship between the community size evolution and leader node influence changes. [Results] The research team exhibited distinct leader characteristics, with a degree variance significantly higher than the degree variance in the random network. 11 out of 15 leaders continuously led the team across all time slots. Approximately 80% of the community’s size and leader centrality showed a linear correlation, with R-values close to 1 and a P-value less than 0.05. [Limitations] This paper simplifies complex leader models by selecting only the most representative expert. [Conclusions] Key figures lead the team over a considerable period, and changes in leader influence are strongly correlated with team size. © 2024 Chinese Academy of Sciences. All rights reserved.