In previous papers it was demonstrated that lower performance groups have a larger size-dependent cumulative advantage for receiving citations than top-performance groups. Furthermore, regardless of performance, larger groups have less not-cited publications. Particularly for the lower performance groups the fraction of not-cited publications decreases considerably with size. These phenomena can be explained with a model in which self-citation acts as a promotion mechanism for external citations. In this article we show that for self-citations similar size-dependent scaling rules apply as for citations but generally the power law exponents are higher for self-citations as compared to citations. We also find that the fraction of self-citations is smaller for the higher performance groups and this fraction decreases more rapidly with increasing journal impact than for lower performance groups. An interesting novel finding is that the variance in the correlation of the number of self-citations with size is considerably less than the variance for external citations. This is a clear indication that size is a stronger determinant for self-citations than for external citations. Both higher and particularly lower performance groups have a size-dependent cumulative advantage for self-citations, but for the higher performance groups only in the lower impact journals and in fields with low citation density.
A Comparison between the China Scientific and Technical Papers and Citations Database and the Science Citation Index in terms of journal hierarchies and inter-journal citation relations
We study how publicity in the science press, in the form of highlighting, affects the citations of research papers. Using multiple linear regression, we quantify the citation advantage associated with several highlighting platforms for papers published in Physical Review Letters (PRL) from 2008-2018. We thus find that the strongest predictor of citation accrual is a Viewpoint in Physics magazine, followed by a Research Highlight in Nature, an Editors' Suggestion in PRL, and a Research Highlight in Nature Physics. A similar hierarchical pattern is found when we search for extreme, not average, …
The decline in the concentration of citations, 1900-2007
本文对最近的研究（Evans，2008）提出了挑战，该研究报告称，随着文章和期刊的在线可用性，被引用的科学文献的集中度会增加。本文使用汤森路透的Web of Science，分析了1900年至2005年期间发表的论文的引用集中度（两年和五年的引用窗口）的变化。使用三种集中度指标：至少收到一次引用的论文百分比（引用论文）;需要占引用的20%，50%和80%的论文百分比;以及Herfindahl-Hirschman指数。这些措施用于四大学科：自然科学和工程，医学领域，社会科学和人文科学。所有这些措施收敛，并表明，与埃文斯的报告相反，引文的分散实际上是增加的。
The study of citations in the scientific literature crosses the boundaries between the traditional branches of science and stands on its own as a most profitable research field dubbed the `science of science'. Although the understanding of the citation histories of individual papers involves many intangible factors, the basic assumption that citations beget citations can explain most features of the empirical citation patterns. Here we use the SIR epidemic model as a mechanistic model for the citation dynamics of well-cited papers published in selected journals of the American Physical Society…
How to evaluate universities in terms of their relative citation impacts: Fractional counting of citations and the normalization of differences among disciplines
We study how publicity, in the form of highlighting in the science press, affects the citations of research papers. After a brief review of prior work, we analyze papers published in Physical Review Letters (PRL) that are highlighted across eight different platforms. Using multiple linear regression we identify how each platform contributes to citations. We also analyze how frequently the highlighted papers end up in the top 1% cited papers in their field. We find that the strongest predictors of medium-term citation impact -- up to 7 years post-publication -- are Viewpoints in Physics, follow…
Network-based statistical comparison of citation topology of bibliographic databases
现代书目数据库为科学研究及其评价提供了基础。虽然它们的内容和结构大不相同，但对其可靠性只有非正式的概念。在这里，我们比较了引文网络的拓扑结构的一致性提取的六个流行的书目数据库，包括Web of Science，CiteSeer和arXiv. org的网络进行评估，通过丰富的本地和全球的图形统计。我们首先揭示了一些数据库之间的统计上显着的不一致，就个人统计。例如，DBLP计算机科学参考书目的引入字段蝴蝶结分解由于数据库的覆盖范围而与其他文献有很大不同，而arXiv.org中的引用信息是最详尽的。最后，我们使用临界差异图在多个图统计上比较数据库。DBLP计算机科学书目的引用拓扑与其他文献最不一致，而毫不奇怪，从一致性的角度来看，Web of Science的引用拓扑明显更可靠。本研究可作为文献计量学和科学计量学研究者的参考，也可作为政府和科研机构的科学评价指南。
It is a matter of debate whether a shrinking proportion of scholarly literature is getting most of the references over time. It is also less well understood how a narrowing literature usage would affect the circulation of ideas in the sciences. Here we show, that the utilization of scientific literature follows dual tendencies over time: while a larger proportion of literature is cited at least a few times, citations are also concentrating more on the top of the citation distribution. Parallel to the latter trend, a paper's future importance increasingly depends on its past citation performanc…
Network Science Institute（网络科学研究所）；Northeastern University（东北大学）；Sabanci University（萨班哲大学）；Brigham and Women’s Hospital（布莱根妇女医院）；Harvard Medical School（哈佛医学院）；Central European University（中欧大学）
The present research attempts to identify the impact of retracted papers on previous or subsequent papers. We consider the 5693 retracted papers from 1975 to 2020 indexed in the Web of Science database based on bibliometric methods. We use HistCite, Excel, and SPSS software as technical means. The findings suggest a significant difference between the average number of retracted and unretracted papers when cited in retracted papers. Furthermore, there is a significant difference between the average number of unretracted and retracted papers citing retracted papers. The reasons for the retractio…
Does it Matter Which Citation Tool is Used to Compare the h-index of a Group of Highly Cited Researchers?
由引文索引（Scopus，Google Scholar和Web of Science）检索的h指数用于衡量科学家的科学表现和研究影响力研究，基于科学家的出版物和引文数量。它也很容易获得，可用于科学家的业绩衡量和招聘决定。本研究的目的是调查这三个引文数据库，即Scopus，Google Scholar和Web of Science基于一组高被引研究人员（诺贝尔奖获得者科学家）的h指数的输出和结果之间的差异。本研究采立意抽样方法收集资料。结果表明，Scopus、Google scholar和Web of Science 3个数据库的h指数存在显著性差异，其中Google scholar h指数大于其他2个数据库的h指数。研究还表明，基于Google Scholar和Scopus的h指数之间存在显著的正相关关系。Scopus、Google Scholar和Web of Science的引文索引对科学家h指数的评价有一定的参考价值，但也存在一定的局限性。
We analyze the citation time-series of manuscripts in three different fields of science; physics, social science and technology. The evolution of the time-series of the yearly number of citations, namely the citation trajectories, diffuse anomalously, their variance scales with time $\propto t^{2H}$, where $H\neq 1/2$. We provide detailed analysis of the various factors that lead to the anomalous behavior: non-stationarity, long-ranged correlations and a fat-tailed increment distribution. The papers exhibit high degree of heterogeneity, across the various fields, as the statistics of the highe…
The backbone of science: analysis of citation networks between papers and their sources
Center for Complex Networks and Systems Research (CNetS), Indiana University（印第安纳大学复杂网络与系统研究中心）；Institute of Complex Systems (UBICS) and Department of Condensed Matter Physics, University of Barcelona（巴塞罗那大学复杂系统研究所和凝聚态物理系）；Department of Computer Science, Loyola University Chicago（芝加哥洛约拉大学计算机科学系）
Science progresses by building upon previous discoveries. It is commonly believed that the impact of scientific papers, as measured by citations, is positively correlated with the impact of past discoveries built upon. However, analyzing over 30 million papers and nearly a billion citations across multiple disciplines, we find that there is a long-term positive citation correlation, but a negative short-term correlation. We demonstrate that the key to resolving this paradox lies in a new concept, called "capacity", which captures the amount of originality remaining for a paper. We find there i…
Newton's centuries-old wisdom of standing on the shoulders of giants raises a crucial yet underexplored question: Out of all the prior works cited by a discovery, which one is its giant? Here, we develop a novel, discipline-independent method to identify the giant for any individual paper, allowing us to systematically examine the role and characteristics of giants in science. We find that across disciplines, about 95% of papers stand on the shoulders of giants, yet the weight of scientific progress rests on relatively few shoulders. Defining a new measure of giant index, we find that, while p…
Demonstrating the practical value of public research has been an important subject in science policy. Here we present a detailed study on the evolution of the citation linkage between life science related patents and biomedical research over a 37-year period. Our analysis relies on a newly-created dataset that systematically links millions of non-patent references to biomedical papers. We find a large disparity in the volume of science linkage among technology sectors, with biotechnology and drug patents dominating it. The linkage has been growing exponentially over a long period of time, doub…
