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Measurement is a complicated but very necessary task. Many indices have been created in an effort to define the quality of knowledge produced but they have attracted strong criticism, having become synonymous with individualism, competition…
We submit newly developed citation impact indicators based not on arithmetic averages of citations but on percentile ranks. Citation distributions are-as a rule-highly skewed and should not be arithmetically averaged. With percentile ranks,…
A simple abstract model is developed as a parallel experimental basis for the aim of exploring the differences of journal impact factors, particularly between different disciplines. Our model endeavors to simulate the publication and…
Assessing the importance of individual features in Machine Learning is critical to understand the model's decision-making process. While numerous methods exist, the lack of a definitive ground truth for comparison highlights the need for…
A method for the multifidelity Monte Carlo (MFMC) estimation of statistical quantities is proposed which is applicable to computational budgets of any size. Based on a sequence of optimization problems each with a globally minimizing…
Is more always better? We address this question in the context of bibliometric indices that aim to assess the scientific impact of individual researchers by counting their number of highly cited publications. We propose a simple model in…
The use of quantitative indicators of scientific productivity seems now quite widespread for assessing researchers and research institutions. There is a general perception, however, that these indicators are not necessarily representative…
The phenomenon of rankings is intimately related with the government interest in fiscalizing the research outputs of universities. New forms of managerialism have been introduced into the higher education system, leading to an increasing…
In growing numbers, scholars are integrating social media tools like blogs, Twitter, and Mendeley into their professional communications. The online, public nature of these tools exposes and reifies scholarly processes once hidden and…
Citation metrics serve as the cornerstone of scholarly impact evaluation despite their well-documented vulnerability to inflation through self-citation practices. This paper introduces the Self-Citation Adjusted Index (SCAI), a…
A lot of attention has been devoted to multimedia indexing over the past few years. In the literature, we often consider two kinds of fusion schemes: The early fusion and the late fusion. In this paper we focus on late classifier fusion,…
In their article, entitled "Towards a new crown indicator: some theoretical considerations," Waltman et al. (2010; at arXiv:1003.2167) show that the "old crown indicator" of CWTS in Leiden was mathematically inconsistent and that one should…
The most commonly used publication metrics for individual researchers are the the total number of publications, the total number of citations, and Hirsch's $h$-index. Each of these is cumulative, and hence increases throughout a…
It is shown that under certain circumstances in particular for small datasets the recently proposed citation impact indicators I3(6PR) and R(6,k) behave inconsistently when additional papers or citations are taken into consideration. Three…
Bibliometric indicators such as journal impact factors, h-indices, and total citation counts are algorithmic artifacts that can be used in research evaluation and management. These artifacts have no meaning by themselves, but receive their…
The contribution to pushing the boundaries of knowledge is a critical metric for evaluating the research performance of countries and institutions, which in many cases is not revealed by common bibliometric indicators. The Rk-index was…
The importance of collaboration in research is widely accepted, as is the fact that articles with more authors tend to be more cited. Nevertheless, although previous studies have investigated whether the apparent advantage of collaboration…
Mixtures of factor analysers (MFA) models represent a popular tool for finding structure in data, particularly high-dimensional data. While in most applications the number of clusters, and especially the number of latent factors within…
In this article we consider a Monte Carlo-based method to filter partially observed diffusions observed at regular and discrete times. Given access only to Euler discretizations of the diffusion process, we present a new procedure which can…
The performance of a binary classifier is described by a confusion matrix with four entries: the number of true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN). The Matthews Correlation Coefficient (MCC),…