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Related papers: A simple model for citation curve

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Citation parsing is fundamental for search engines within academia and the protection of intellectual property. Meticulous extraction is further needed when evaluating the similarity of documents and calculating their citation impact.…

Digital Libraries · Computer Science 2018-05-23 Niall Martin Ryan

I propose the coefficient, $t_h$, and its modification $N_t$ which in a simple way reflect dynamics of scientific activity of an individual researcher. I determine $t_h$ as a time period (from some moment in the past till the present…

Physics and Society · Physics 2007-05-23 S. B. Popov

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, $P(k) \propto k^{-\alpha}$, with…

Physics and Society · Physics 2009-11-07 S. Lehmann , B. Lautrup , A. D. Jackson

This paper analyzes publication efficiency in terms of Hirsch-index or h-index and total citations, with an analogy to the Carnot efficiency used in thermodynamics. Such publication efficiency, with typical value of 30%, can be utilized to…

Digital Libraries · Computer Science 2017-08-29 Abhisek Ukil

Diagrams are often used in scholarly communication. We analyse a corpus of diagrams found in scholarly computational linguistics conference proceedings (ACL 2017), and find inclusion of a system diagram to be correlated with higher numbers…

Digital Libraries · Computer Science 2022-11-22 Guy Clarke Marshall , Caroline Jay , Andre Freitas

For the study of citation networks, a challenging problem is modeling the high clustering. Existing studies indicate that the promising way to model the high clustering is a copying strategy, i.e., a paper copies the references of its…

Physics and Society · Physics 2015-03-19 Fu-Xin Ren , Xue-Qi Cheng , Hua-Wei Shen

Model explainability is crucial for human users to be able to interpret how a proposed classifier assigns labels to data based on its feature values. We study generalized linear models constructed using sets of feature value rules, which…

Machine Learning · Statistics 2023-11-06 Sanjeeb Dash , Soumyadip Ghosh , Joao Goncalves , Mark S. Squillante

Classifying researchers according to the quality of their published work rather than the quantity is a curtail issue. We attempt to introduce a new formula of the percentage range to be used for evaluating qualitatively the researchers'…

Digital Libraries · Computer Science 2013-05-28 Mahmoud Abdel-Aty

We introduce and analyse a simple probabilistic model of article production and citation behavior that explicitly assumes that there is no decline in citability of a given article over time. It makes predictions about the number and age of…

Digital Libraries · Computer Science 2023-05-02 Fatemeh Ghaffari , Mark C. Wilson

Scholarly impact may be metricized using an author's total number of citations as a stand-in for real worth, but this measure varies in applicability between disciplines. The detail of the number of citations per publication is nowadays…

Digital Libraries · Computer Science 2018-09-06 Peter T. Breuer , Jonathan P. Bowen

The h-index can be used as a predictor of itself. However, the evolution of the h-index with time is shown in the present investigation to be dominated for several years by citations to previous publications rather than by new scientific…

Physics and Society · Physics 2013-09-19 Michael Schreiber

A central question in science of science concerns how time affects citations. Despite the long-standing interests and its broad impact, we lack systematic answers to this simple yet fundamental question. By reviewing and classifying prior…

Physics and Society · Physics 2018-12-13 Yian Yin , Dashun Wang

Citations in science are being studied from several perspectives, among which approaches such as scientometrics and science of science. In this chapter I briefly review some of the literature on citations, citation distributions and models…

Digital Libraries · Computer Science 2025-05-12 V. A. Traag

A recent analysis of scientific publication and patent citation networks by Park et al. (Nature, 2023) suggests that publications and patents are becoming less disruptive over time. Here we show that the reported decrease in disruptiveness…

Digital Libraries · Computer Science 2024-12-03 Alexander M. Petersen , Felber Arroyave , Fabio Pammolli

A multi-parametric family of stretch exponential distributions with various power law tails is introduced and is shown to describe adequately the empirical distributions of scientific citation of individual authors. The four-parametric…

Physics and Society · Physics 2016-05-13 O. S. Garanina , M. Yu. Romanovsky

Changes in citation distributions over 100 years can reveal much about the evolution of the scientific communities or disciplines. The prevalence of uncited papers or of highly-cited papers, with respect to the bulk of publications,…

Physics and Society · Physics 2008-10-09 Matthew L. Wallace , Vincent Larivière , Yves Gingras

A large literature specifies conditions under which the information complexity for a sequence of numerical problems defined for dimensions $1, 2, \ldots$ grows at a moderate rate, i.e., the sequence of problems is tractable. Here, we focus…

Numerical Analysis · Mathematics 2024-04-24 Onyekachi Emenike , Fred J. Hickernell , Peter Kritzer

In this paper we present "citation success index", a metric for comparing the citation capacity of pairs of journals. Citation success index is the probability that a random paper in one journal has more citations than a random paper in…

Digital Libraries · Computer Science 2016-12-23 Staša Milojević , Filippo Radicchi , Judit Bar-Ilan

One compelling use of citation networks is to characterize papers by their relationships to the surrounding literature. We propose a method to characterize papers by embedding them into two distinct "co-factor" spaces: one describing how…

Methodology · Statistics 2025-10-07 Alex Hayes , Karl Rohe

Learning Gibbs distributions using only sufficient statistics has long been recognized as a computationally hard problem. On the other hand, computationally efficient algorithms for learning Gibbs distributions rely on access to full sample…

Machine Learning · Computer Science 2026-02-16 Abhijith Jayakumar , Shreya Shukla , Marc Vuffray , Andrey Y. Lokhov , Sidhant Misra
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