Identification of core sub-team on scientific collaboration networks with Shapley method.

ABSTRACT: Identifying the core sub-teams that drive productivity in scientific collaboration networks is essential for research evaluation and team management. However, existing methods typically rank individual researchers by bibliometric impact or select structurally cohesive clusters, but rarely account for both collaboration patterns and joint scientific output. To address this limitation, we propose a novel two-dimensional framework that integrates network topology with research performance to identify core sub-teams. Specifically, we measure each sub-team's marginal structural contribution using the Shapley value and quantify its collective impact using a sub-team H-index. To efficiently identify high-contributing sub-teams, we employ the Monte Carlo Tree Search algorithm, along with an approx

SUBMITTER: Zhou L 

PROVIDER: S-EPMC12453774 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature