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Scientometric engineering: Revealing spatiotemporal citation dynamics via open eprints
arXiv - CS - Computers and Society Pub Date : 2021-06-09 , DOI: arxiv-2106.05027
Keisuke Okamura

With the ever-increasing speed and volume of knowledge production and consumption, scholarly communication systems have been rapidly transformed into digitised and networked open ecosystems, where preprint servers have played a pivotal role. However, evidence is scarce regarding how this paradigm shift has affected the dynamics of collective attention on scientific knowledge. Herein, we address this issue by investigating the citation dynamics of more than 1.5 million eprints on arXiv, the most prominent and oldest eprint archive. The discipline-average citation history curves are estimated by applying a nonlinear regression model to the long-term citation data. The revealed spatiotemporal characteristics, including the growth and obsolescence patterns, are shown to vary across disciplines, reflecting the different publication and citation practices. The results are used to develop a spatiotemporally normalised citation index, called the $\gamma$-index, with an approximately normal distribution. It can be used to compare the citational impact of individual papers across disciplines and time periods, providing a less biased measure of research impact than those widely used in the literature and in practice. Further, a stochastic model for the observed spatiotemporal citation dynamics is derived, reproducing both the Lognormal Law for the cumulative citation distribution and the time trajectory of average citations in a unified formalism.

中文翻译:

科学计量工程学:通过开放电子印本揭示时空引文动态

随着知识生产和消费的速度和数量的不断增加,学术交流系统已迅速转变为数字化、网络化的开放生态系统,其中预印本服务器发挥了关键作用。然而,关于这种范式转变如何影响集体关注科学知识的动态,证据很少。在此,我们通过调查 arXiv 上超过 150 万份 eprint 的引文动态来解决这个问题,arXiv 是最著名和最古老的 eprint 档案。学科平均引文历史曲线是通过对长期引文数据应用非线性回归模型来估计的。所揭示的时空特征,包括增长和过时模式,在不同学科中有所不同,反映了不同的发表和引用实践。结果用于开发一个时空归一化的引文索引,称为 $\gamma$-index,具有近似正态分布。它可用于比较跨学科和跨时间段的单篇论文的引用影响,与文献和实践中广泛使用的衡量指标相比,它提供的研究影响衡量指标偏差较小。此外,推导出观察到的时空引用动态的随机模型,以统一的形式再现累积引用分布的对数正态定律和平均引用的时间轨迹。它可用于比较跨学科和跨时间段的单篇论文的引用影响,与文献和实践中广泛使用的衡量指标相比,它提供的研究影响衡量指标偏差较小。此外,推导出观察到的时空引用动态的随机模型,以统一的形式再现累积引用分布的对数正态定律和平均引用的时间轨迹。它可用于比较跨学科和跨时间段的单篇论文的引用影响,与文献和实践中广泛使用的衡量指标相比,它提供的研究影响衡量指标偏差较小。此外,推导出观察到的时空引用动态的随机模型,以统一的形式再现累积引用分布的对数正态定律和平均引用的时间轨迹。
更新日期:2021-06-10
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