A1391
Title: Modeling academic collaboration networks using hypergraph theory: A large-scale scientometric analysis of Scopus data
Authors: Tzu-Yin Chen - National Taiwan University (Taiwan) [presenting]
Frederick Kin Hing Phoa - Academia Sinica (Taiwan)
Abstract: Academic collaboration patterns from 2010 to 2024 are investigated through the lens of hypergraph theory using bibliometric data extracted from the Scopus database. Structural characteristics and temporal evolution of co-authorship networks are analyzed, with hypergraph representations naturally capturing multi-author collaborations and providing a more realistic framework for modeling academic communities compared to conventional graph-based approaches. Empirical analyses are conducted on four representative subject areas in Scopus: Dentistry (Health Sciences), Immunology and Microbiology (Life Sciences), Computer Science (Physical Sciences), and Arts (Social Sciences). For each subject, cumulative collaboration trends and five-year moving-window densities are examined to characterize temporal dynamics. Collaboration structures before and after the COVID-19 pandemic (2020-2022) are compared to evaluate the impact of global disruptions on research collaboration. Special attention is given to changes in single-author publications as indicators of independent research activity. The main contribution lies in integrating hypergraph theory with bibliometric analysis to provide a richer representation of scholarly collaboration. The proposed framework can be extended to incorporate additional bibliometric indicators and applied to other scientific disciplines and large-scale academic databases.
