Analysis of Geo-Economic Distribution of Scientific Publications Citation and Self-Citation Standardized Indices Based on Machine Learning

Abstract

The article dwells upon the logical order of processing, transformation and synthesis of data windows, their visualization and analysis for geo - economic distribution research of articles authorship numerical characteristics, their citation, estimation, lack of linear and nonlinear relationships between individual parameters of author and percentage of self-citation. The work demonstrates the possibility of using new and classical methods of data visualization to study patterns, relationships between numerical and nominal data as well as methods of using conventional multilayer perceptrons to search for nonlinear relationships between multiple parameters. Open source software designed to build the necessary representations of data and models is the important part of the investigation. © 2022 Copyright for this paper by its authors.