Michael J. Bommarito, Daniel Martin Katz, Jon Zelner, James H. Fowler
备注：
7 pages, 5 figures. Revision: Added application to the network of the first quarter-century of Supreme Court citations. Revision 2: Significantly expanded, includes application on random model as well
Acyclic digraphs arise in many natural and artificial processes. Among the broader set, dynamic citation networks represent a substantively important form of acyclic digraphs. For example, the study of such networks includes the spread of ideas through academic citations, the spread of innovation through patent citations, and the development of precedent in common law systems. The specific dynamics that produce such acyclic digraphs not only differentiate them from other classes of graphs, but also provide guidance for the development of meaningful distance measures. In this article, we develop and apply our sink distance measure together with the single-linkage hierarchical clustering algorithm to both a two-dimensional directed preferential attachment model as well as empirical data drawn from the first quarter century of decisions of the United States Supreme Court. Despite applying the simplest combination of distance measures and clustering algorithms, analysis reveals that more accurate and more interpretable clusterings are produced by this scheme.
This paper analyses the influence of geographic distance on knowledge flows, measured through citations to scientific publications. Previous works using the same approach are limited to single disciplines. In this study, we analyse the Italian scientific production in all disciplines matured in the period 2010-2012. To calculate the geographic distances between citing and cited publications, each one is associated with a "prevalent" territory on the basis of the authors' affiliations. The results of the application of a gravity model, estimated using ordinary least squares regression, show tha…
Studies of bibliographic data suggest a strong correlation between the growth of citation networks and their corresponding co-authorship networks. We explore the interdependence between evolving citation and co-authorship networks focused on the publications, by Indian authors, in American Physical Society journals between 1970 and 2013. We record interactions between each possible pair of authors in two ways: first, by tracing the change in citations they exchanged and, second, by tracing the shortest path between authors in the co-authorship network. We create these data for every year of th…
This study proposes the usage of a method called VoteRank, created by Zhang et al. (2016), to identify influential nodes on patent citation networks. In addition, it proposes enhanced VoteRank algorithms, extending the Zhang et al. work. These novel algorithms comprise a reduction on the voting ability of the nodes affected by a chosen spreader if the nodes are distant from the spreader. One method uses a reduction factor that is linear regarding the distance from the spreader, which we called VoteRank-LRed. The other method uses a reduction factor that is exponential concerning the distance f…
This paper investigates the impact of institutes and papers over time based on the heterogeneous institution-citation network. A new model, IPRank, is introduced to measure the impact of institution and paper simultaneously. This model utilises the heterogeneous structural measure method to unveil the impact of institution and paper, reflecting the effects of citation, institution, and structural measure. To evaluate the performance, the model first constructs a heterogeneous institution-citation network based on the American Physical Society (APS) dataset. Subsequently, PageRank is used to qu…
To quantify the mechanism of a complex network growth we focus on the network of citations of scientific papers and use a combination of the theoretical and experimental tools to uncover microscopic details of this network growth. Namely, we develop a stochastic model of citation dynamics based on copying/redirection/triadic closure mechanism. In a complementary and coherent way, the model accounts both for statistics of references of scientific papers and for their citation dynamics. Originating in empirical measurements, the model is cast in such a way that it can be verified quantitatively …
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。
We study the statistics of citations made to the indexed Science journals in the Journal Citation Reports during the period 2004-2013 using different measures. We consider different measures which quantify the impact of the journals. To our surprise, we find that the apparently uncorrelated measures, even when defined in an arbitrary manner, show strong correlations. This is checked over all the years considered. Impact factor being one of these measures, the present work raises the question whether it is actually a nearly perfect index as claimed often. In addition we study the distributions …
It is widely recognized that citation counts for papers from different fields cannot be directly compared because different scientific fields adopt different citation practices. Citation counts are also strongly biased by paper age since older papers had more time to attract citations. Various procedures aim at suppressing these biases and give rise to new normalized indicators, such as the relative citation count. We use a large citation dataset from Microsoft Academic Graph and a new statistical framework based on the Mahalanobis distance to show that the rankings by well known indicators, i…
Bibliographic coupling (BC) and co-citation (CC) are the two most common citation-based coupling measures of similarity between scientific items. One can interpret these measures as second-neighbor relations distinguished by the direction of the citation: BC is a similarity between two citing items, whereas CC is that between two cited items. A previous study proposed a two-layer node split network that can emulate clusters of coupling measures in a computationally efficient manner; however, the lack of intralayer links makes it impossible to obtain exact similarities. Here, we propose novel m…
We have constructed a fitness parameter, characterizing the intrinsic attractiveness for patents to be cited, from attributes of the associated inventions known at the time a patent is granted. This exogenously obtained fitness is shown to determine the temporal growth of the citation network in conjunction with mechanisms of preferential attachment and obsolescence-induced ageing that operate without reference to characteristics of individual patents. Our study opens a window on understanding quantitatively the interplay of the rich-gets-richer and fit-gets-richer paradigms that have been sug…
Journal rankings are widely used and are often based on citation data in combination with a network perspective. We argue that some of these network-based rankings can produce misleading results. From a theoretical point of view, we show that the standard network modelling approach of citation data at the journal level (i.e., the projection of paper citations onto journals) introduces fictitious relations among journals. To overcome this problem, we propose a citation path perspective, and empirically show that rankings based on the network and the citation path perspective are very different.…
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）
Scientists are embedded in social and information networks that influence and are influenced by the quality of their scientific work, its impact, and the recognition they receive. Here we quantify the systematic relationship between a scientist's position in the network of scientific collaborations and the citations they receive. As expected, we find that authors closer to others in this network are, on average, more highly cited than those further away from others. We construct a novel indicator, the s-index, that explicitly captures performance linked to network position along two compliment…
The academic publishing world is changing significantly, with ever-growing numbers of publications each year and shifting publishing patterns. However, the metrics used to measure academic success, such as the number of publications, citation number, and impact factor, have not changed for decades. Moreover, recent studies indicate that these metrics have become targets and follow Goodhart's Law, according to which "when a measure becomes a target, it ceases to be a good measure." In this study, we analyzed over 120 million papers to examine how the academic publishing world has evolved over t…
Complex-valued information entropy measure for networks with directed links (digraphs). Application to citations by community agents with opposite opinions
