What is it about?

Scientometry became an essential tool for evaluating scientific's qualities. Here we complement the formal statistical analysis with a new approach entirely based on disambiguated networks to study the Chaos journal's evolution in aspects such as diversity, collaboration, influence, and productivity considering authors, countries, and topics.

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Why is it important?

Analysis from different network perspectives of authors, countries and topics in the CHAOS journal uncovers interesting evolution of diversity, collaboration, influence and productivity. The directed and weighted networks in nodes and links are essential for our study, allowing us to identify more objective qualities of the actors in the networks. The concept of time-variable weighted networks and the nodes' relevance even if they might be isolated permits us to get a primary evaluation of the system's robustness.


This work emerges as a fruitful collaboration between coauthors that have been working on a wide variety of systems. It is desirable that the new approach considered in this work and the resulting scientometric tools will be used for assessing more objectively scientific qualities in other systems. The concept of nodes' relevance might also be helpful for general network analysis.

Gonzalo Marcelo Ramirez-Avila
Instituto de Investigaciones Fisicas, Universidad Mayor de San Andres

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This page is a summary of: Scientometric analysis of the Chaos journal (1991–2019): From descriptive statistics to complex networks viewpoints, Chaos An Interdisciplinary Journal of Nonlinear Science, April 2021, American Institute of Physics,
DOI: 10.1063/5.0044719.
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