BIBLIOMETRIC ANALYSIS OF NEURAL BASIS EXPANSION ANALYSIS FOR INTERPRETABLE TIME SERIES (N-BEATS) FOR RESEARCH TREND MAPPING

Abstract

Bibliometrics is the statistical analysis of articles, books, and other forms of publication. The bibliometrics analysis is performed with data on the number and authorship of scientific publications and articles, and citations to measure the work of individuals or groups of researchers, organizations, and countries to identify national and international networks and map developments in new multidisciplinary fields of science and technology. In addition, bibliometrics assesses and maps the research, organization, and country of researchers at a given time period. The Bibliometric analysis also has advantages which include mapping relationships between concepts, mapping research directions or trends, mapping state of the art (the novelty of the results of research conducted), and providing insights related to fields, topics, and research problems for future works. This study aims to determine the growth and development of N-BEATS publications, their distribution, variable keywords, and author collaboration using a bibliometric network. The research method used in this paper, through screening of articles obtained from the Scopus database page in 2008-2022, is used for citations in the form of metrics. At the same time, they are visualizing the metadata with VOSviewer. Data was collected from the direct science database with the keyword N-BEATS. The results show that 2022 has the highest number of publications, reaching 310 publications (14.90%). The distribution of research publications on N-BEATS shows a perfect distribution. Terms in the N-BEATS variable that often appear and are associated with other variables.