Local Scientific Collaboration Networks: A Case Study

Abstract

This study analyzes local scientific collaboration through weighted co-authorship networks of two Hungarian university faculties using the domestic scientific bibliography (MTMT) data. Researchers are modeled as nodes and joint publications define weighted edges. Network metrics and a permutation-based statistical framework are applied to compare structures. While some global properties are similar, significant differences appear in degree and strength distributions, indicating distinct collaboration patterns independent of faculty size. The results highlight structural features that cannot be captured without a network-based approach. These insights are valuable for institutional strategy and decision-making in fostering collaboration.