 Analysis of reference and citation copying in evolving bibliographic networksPradumn Kumar Pandey, Mayank Singh, Pawan Goyal, Animesh Mukherjee and Soumen Chakrabarti Journal of Informetrics, 2020, vol. 14, issue 1 Abstract: Extensive literature demonstrates how the copying of references (links) can lead to the emergence of various structural properties (e.g., power-law degree distribution and bipartite cores) in bibliographic and other similar directed networks. However, it is also well known that the copying process is incapable of mimicking the number of directed triangles in such networks; neither does it have the power to explain the obsolescence of older papers. In this paper, we propose RefOrCite, a new model that allows for copying of both the references 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, RefOrCite differs from the Forest Fire (FF) model in ways that makes RefOrCite amenable to mean-field analysis for degree distribution, triangle count, and densification. Empirically, RefOrCite gives the best overall agreement with observed degree distribution, triangle count, diameter, h-index, and the growth of citations to newer papers. Keywords: Citation network; Preferential attachment; Growth models (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:14:y:2020:i:1:s1751157719303384 DOI: 10.1016/j.joi.2019.101003 Access Statistics for this article Journal of Informetrics is currently edited by Leo Egghe More articles in Journal of Informetrics from Elsevier |
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