8卷 第5期
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
纸质出版日期： 2024-05-24 ，
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Machine learning fusion and applications in the financial research field from the multi-level bibliometric perspective[J]. 国际教育与发展（英文版）, 2024,8(5):184-199.
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.
Machine learning fusion and applications in the financial research field from the multi-level bibliometric perspective[J]. 国际教育与发展（英文版）, 2024,8(5):184-199. DOI： 10.47297/wspiedWSP2516-250031.20240805.
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.
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.
Credit scoringForecastingCollaborative networkFinancial research field
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