Citation Network Analysis in Scientific Research at Private University

This study applies Social Network Analysis (SNA) to explore research collaboration within a private Indonesian university by analyzing a citation network of co-authored publications. SNA provides a robust framework for understanding the relationships between scholars, helping to map collaboration patterns, identify influential researchers, and track the flow of knowledge within academic communities. Citation Network Analysis (CNA), a subset of Social Network Analysis (SNA), is particularly useful for investigating how academic work references and influences other publications. In the context of the university’s growing research output, this study leverages centrality metrics and modularity-based community detection to uncover the structural dynamics of scholarly collaboration. The analysis reveals a highly centralized network structure, where key individuals serve as central hubs and strategic bridges between research communities. The leading author stands out by dominating all primary centrality measures, illustrating their crucial role in maintaining the network’s cohesion and facilitating knowledge exchange. The study also uncovers a core-periphery topology, where more peripheral figures support a dense core group of researchers. Visualization tools and structural metrics such as eccentricity further demonstrate a compact, interconnected network, with most researchers accessible within a few steps of each other. These findings provide practical insights for enhancing institutional research strategies, promoting academic collaboration, and improving scholar visibility. Ultimately, the study demonstrates the utility of SNA and CNA in guiding data-driven decisions to strengthen research networks and elevate institutional performance.