arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1302.4095physics.soc-phcs.DLcs.SIphysics.data-an
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引文网络拓扑结构的三特征模型及作者知名度对其h指数的影响

Three-feature model to reproduce the topology of citation networks and the effects from authors' visibility on their h-index

Diego R. Amancio, Osvaldo N. Oliveira, Luciano da F. Costa

摘要:

在引文网络中,各种因素被认为支配着参考文献的选择,但精确地定量确定它们的重要性仍然是难以捉摸的。在本文中,我们表明,三个因素可以占引用模式的引用网络的两个主题,即“石墨烯”和“复杂网络”,从而允许一个复制的拓扑特征的论文建立的节点和边的引用。最相关的因素是内容相似性,而其他两个-度(即引用计数)和{出版年龄}根据研究的主题具有不同的重要性。这种依赖性表明,其他因素可能发挥作用。事实上,凭直觉,人们应该期望作者和/或机构的声誉(或知名度)会影响引用模式,而这只是通过与这种声誉相关的程度间接考虑的。由于声誉的信息是不容易获得的,我们模拟了它对人工引用网络的影响,考虑两个社区具有不同的适应度(可见性)参数。假设一个社区的适应值是另一个社区的两倍,这相当于一篇论文被引用的概率是两倍。虽然具有较大适应度的社区中的作者的h指数随着时间的推移而演变,其值略高于控制网络(不考虑适应度),但对于具有较小适应度的社区,注意到了剧烈的影响。

英文摘要:

Various factors are believed to govern the selection of references in citation networks, but a precise, quantitative determination of their importance has remained elusive. In this paper, we show that three factors can account for the referencing pattern of citation networks for two topics, namely "graphenes" and "complex networks", thus allowing one to reproduce the topological features of the networks built with papers being the nodes and the edges established by citations. The most relevant factor was content similarity, while the other two - in-degree (i.e. citation counts) and {age of publication} had varying importance depending on the topic studied. This dependence indicates that additional factors could play a role. Indeed, by intuition one should expect the reputation (or visibility) of authors and/or institutions to affect the referencing pattern, and this is only indirectly considered via the in-degree that should correlate with such reputation. Because information on reputation is not readily available, we simulated its effect on artificial citation networks considering two communities with distinct fitness (visibility) parameters. One community was assumed to have twice the fitness value of the other, which amounts to a double probability for a paper being cited. While the h-index for authors in the community with larger fitness evolved with time with slightly higher values than for the control network (no fitness considered), a drastic effect was noted for the community with smaller fitness.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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