On the Scale-Free Property of Citation Networks: An Empirical Study 2024

Citation networks have been thought to exhibit scale-free property for many years; however, this assertion has been doubted recently. In this paper, we conduct extensive experiments to resolve this controversial issue. We firstly demonstrate the scale-free property in scale-free networks sampled from the popular Barabasi-Albert (BA) model. To this end, we employ a merged rank distribution, which is divided into outliers, power-law segment, and non-power-law data, to characterize network degrees, and propose a random sample consensus (RANSAC)-based method to identify power-law segments from merged rank distributions, and use the Kolmogorov-Smirnov (KS) test to examine the scale-free property in power-law segments. Subsequently, we apply the same methods to examine the scale-free property in real-world citation networks. Experimental results confirm the scale-free property in citation networks and attribute previous skepticism to the presence of outliers.

Autores	Pedraja-Rejas, L; Rodriguez-Ponce, E; Munoz-Fritis, C; Laroze, D
Título	Sustainable Development Goals and Education: A Bibliometric Review-The Case of Latin America
Afiliaciones	Universidad de Tarapaca; Universidad de Tarapaca
Año	2023
DOI	10.3390/su15129833
Tipo de acceso abierto	gold
Referencia	WOS:001015693100001
Artículo obtenido de:	WOS

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On the Scale-Free Property of Citation Networks: An Empirical Study

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