arXivDaily arXiv每日学术速递 周一至周五更新
arXiv physics/0211010physics.soc-phhep-phhep-th
收藏

高能物理引文网络

Citation Networks in High Energy Physics

S. Lehmann, B. Lautrup, A. D. Jackson

摘要:

对SPIRES数据库构成的引文网络进行了实证研究。SPIRES数据库中给定论文有$k$引用的概率可用简单的幂律$P(k) \propto k^{-α}$来描述,$k$引用少于50次的概率为$α\approx 1.2$,引用多于50次的概率为$α\approx 2.3$。两个模型都代表了数据,一个产生幂律,一个产生拉伸指数。根据目前的经验,不可能区分这些模式。对高能物理各学科引文分布的考察表明,高能物理各学科的引文模式形成了一个非常均匀的网络。此外,我们利用引文分布的知识来证明所选择的个人和机构的引文记录是通过随机抽取所得到的分布来获得的,这是极不可能的。

英文摘要:

The citation network constituted by the SPIRES data base is investigated empirically. The probability that a given paper in the SPIRES data base has $k$ citations is well described by simple power laws, $P(k) \propto k^{-α}$, with $α\approx 1.2$ for $k$ less than 50 citations and $α\approx 2.3$ for 50 or more citations. Two models are presented that both represent the data well, one which generates power laws and one which generates a stretched exponential. It is not possible to discriminate between these models on the present empirical basis. A consideration of citation distribution by subfield shows that the citation patterns of high energy physics form a remarkably homogeneous network. Further, we utilize the knowledge of the citation distributions to demonstrate the extreme improbability that the citation records of selected individuals and institutions have been obtained by a random draw on the resulting distribution.

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。

↑