Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Bibliometric Knowledge Mapping of E-Commerce Platform Operation on Data Mining

Version 1 : Received: 17 December 2020 / Approved: 21 December 2020 / Online: 21 December 2020 (14:24:06 CET)

How to cite: Ye, M.; Li, H. Bibliometric Knowledge Mapping of E-Commerce Platform Operation on Data Mining. Preprints 2020, 2020120529 (doi: 10.20944/preprints202012.0529.v1). Ye, M.; Li, H. Bibliometric Knowledge Mapping of E-Commerce Platform Operation on Data Mining. Preprints 2020, 2020120529 (doi: 10.20944/preprints202012.0529.v1).

Abstract

The e-commerce platform in the digital economy era has evolved into a data platform ecosystem built around data resources and data mining technology systems. The most typical applications of big data are also concentrated in the field of e-commerce. E-commerce companies should first grasp the interactive relationship among the three major factors of data, technology and innovation, e-commerce platform operation is a multidisciplinary research field. It is not easy for researchers to obtain a panoramic view of the knowledge structure in this field. Knowledge graph is a kind of graph that shows the development process and structure relationship of knowledge with the field of knowledge as the object. It is not only a visual knowledge mapping, but also a serialized knowledge pedigree, which provides researchers with a quantitative research method for the development trend of statistics and academic status. The purpose of this research is to help researchers understand the key knowledge, evolutionary trends and research frontiers of current research. This study uses Citespace bibliometric analysis to analyze the data of the Science Net database and finds that: 1) The development of the research field has gone through three stages, and some representative key scholars and key documents have been recognized; 2) the common knowledge mapping of literature The co-occurrence of citations and keywords shows research hotspots; 3) The results of burst detection and central node analysis reveal research frontiers and development trends. Today, the visualization of big data brings different challenges. The abstraction between the world and today's data visualization occurs when the data is captured. Every user sees his own visualization data generated by standardized calculations. At the same time, there are still many controversies in the theoretical model, structure and structural dimensions. This is the direction that future researchers need to further study.

Subject Areas

e-commerce; big data; bibliometric analysis; knowledge mapping

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