分类:Transitive reduction of citation networks

来自Big Physics
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James R. Clough, Jamie Gollings, Tamar V. Loach & Tim S. Evans, Transitive reduction of citation networks, J Complex Netw (2015) 3 (2): 189-203. DOI: https://doi.org/10.1093/comnet/cnu039

Abstract

n many complex networks, the vertices are ordered in time, and edges represent causal connections. We propose methods of analysing such directed acyclic graphs taking into account the constraints of causality and highlighting the causal structure. We illustrate our approach using citation networks formed from academic papers, patents and US Supreme Court verdicts. We show how transitive reduction (TR) reveals fundamental differences in the citation practices of different areas, how it highlights particularly interesting work, and how it can correct for the effect that the age of a document has on its citation count. Finally, we transitively reduce null models of citation networks with similar degree distributions and show the difference in degree distributions after TR to illustrate the lack of causal structure in such models.

总结和评论

这篇文章把网络中一个叫做Transitive Reduction(保连通性去边?)的方法用到了引文网络上,企图来识别关键的引文、不同引文的风格驱动力等模式。

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