Analysis of reference and citation copying in evolving bibliographic networks

Extensive literature demonstrates how the copying of references (links) canlead to the emergence of various structural properties (e.g., power-law degreedistribution and bipartite cores) in bibliographic and other similar directednetworks. However, it is also well known that the copying process is incapableof mimicking the number of directed triangles in such networks; neither doesit have the power to explain the obsolescence of older papers. In this paper,we proposeRefOrCite, a new model that allows for copying of both thereferences from (i.e., out-neighbors of) as well as the citations to (i.e., in-neighbors of) an existing node. In contrast, the standard copying model (CP)only copies references. While retaining its spirit,RefOrCitediffers fromthe Forest Fire (FF) model in ways that makesRefOrCiteamenable tomean-field analysis for degree distribution, triangle count, and densification.Empirically,RefOrCitegives the best overall agreement with observeddegree distribution, triangle count, diameter, h-index, and the growth ofcitations to newer papers.