Dynamic visualization of citation networks showing the influence of scholarly fields over time

Abstract

Citation graphs between scholarly papers can be used to learn about the structure and development of scholarship. We present a generalizable approach to visualizing scholarly influence over time, using a dynamic node-link diagram representing the citation patterns between groups of papers. We combine this approach with hierarchical clustering techniques that exploit the network structure to partition the graph into clusters representing fields and subfields. We use these methods to explore the influence that fields have had on other fields over time.