Library User Behavior Based on a Bipartite Knowledge Interaction Network from the Perspective of Knowledge Ecosystems

This study examines library user behavior and its impact on knowledge flow through the lens of the knowledge ecosystem, using a bipartite network model. By constructing a Bipartite Knowledge Interaction Network based on data from a vocational medical college library, the research defines and evaluates various multidimensionall indicators, such as user activity, information demand distribution, and behavioral diversity. A time-series analysis is employed to explore the dynamic nature of user behavior. The findings show that high-frequency users are key drivers of knowledge flow, demonstrating significantly greater behavioral diversity compared to medium- and low-frequency users. IT and medical resources are most in demand, while resources in the arts and sciences are less frequently accessed. Moreover, user behavior shows a clear correlation with time-specific patterns. These results offer valuable insights and data to help optimize library knowledge services.