Machine learning fusion and applications in the financial research field from the multi-level bibliometric perspective

Shuaikang Miao; Yan Xu

doi:10.47297/wspiedWSP2516-250031.20240805

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Machine learning fusion and applications in the financial research field from the multi-level bibliometric perspective

Volume 8, Issue 5

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Machine learning fusion and applications in the financial research field from the multi-level bibliometric perspective
Machine learning fusion and applications in the financial research field from the multi-level bibliometric perspective
1.School of Logistics and Management Engineering, Yunnan University of Finance and Economics, Kunming 650221, China
2.School of Logistics and Management Engineering, Yunnan University of Finance and Economics, Kunming 650221, China
Vol. 8, Issue 5, Pages: 184-199(2024)
Published： 24 May 2024 ，
DOI：10.47297/wspiedWSP2516-250031.20240805
Accepted：

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Miao Shuaikang,Xu Yan.Machine learning fusion and applications in the financial research field from the multi-level bibliometric perspective[J].Journal of International Education and Development,2024,08(05):184-199.
DOI：

Miao Shuaikang,Xu Yan.Machine learning fusion and applications in the financial research field from the multi-level bibliometric perspective[J].Journal of International Education and Development,2024,08(05):184-199. DOI： 10.47297/wspiedWSP2516-250031.20240805.

摘要

Abstract

Artificial intelligence and machine learning provide the financial industry with a variety of new technologies

bringing new opportunities for its further development. The application of machine learning in financial field has been great attracting attention from scholars around the world. It is necessary to analyze the status quo and emerging trends in this research area

specifically for beginners who are interested in this research field. Similarly

this paper mainly focuses on the current state of machine learning in finance and its applications based on 3951 papers on Web of Science from 1991 to 2022 by using Citespace to make a research collaboration network analysis of the cited literature review and the burst detection. From the above analysis

this paper has the following findings. First

although machine learning is widely used in the financial field

in terms of application

the number of published papers in various fields is still small

and it is necessary to further deepen research in various fields. Second

the relationship between major researchers and research units is not strong

and the cooperative relationship is not obvious. Third

through the analysis of keywords

it can be found that the main research contents are "forecasting"

"convolutional neural network"

"credit scoring" and "text mining"

and these keywords are also the focus of current research. This paper gives a comprehensive analysis of research on machine learning in finance and provides some inspiration for researchers in the field to do further study.

关键词

Keywords

Credit scoringForecastingCollaborative networkFinancial research field

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