A Comparison Study of Measures to Quantify the Evolution of Prolific Research Teams

Abstract

Scientific research teams play an increasingly significant role in scientific activities. To better understand the dynamic evolution process of research teams, we explored measures that quantify the evolution of prolific research teams. We collected our data from the Web of Science in the field of artificial intelligence, and applied the label propagation algorithm to identify research teams in the co-authorship network. The Top 1‰ prolific teams were selected as our research object, whose node stability and two types of edge stabilities were measured. The results show that prolific teams are much more stable during the evolution process, in terms of both member and membership stability. The measure of stability has varying degrees of impact on teams with different sizes, and small-sized teams get considerably different stability results by different measures.