Comprehensive review of text-mining applications in finance

被引:54
|
作者
Gupta, Aaryan [1 ]
Dengre, Vinya [1 ]
Kheruwala, Hamza Abubakar [1 ]
Shah, Manan [2 ]
机构
[1] Nirma Univ, Dept Comp Sci, Ahmadabad, Gujarat, India
[2] Pandit Deendayal Petr Univ, Sch Technol, Dept Chem Engn, Gandhinagar 382007, Gujarat, India
关键词
Text mining; Machine learning; Financial forecasting; Sentiment analysis; Text classification; Corporate finance; DECISION-SUPPORT; NEURAL-NETWORKS; SENTIMENT; PREDICTION; CLASSIFICATION; SYSTEM; TRENDS;
D O I
10.1186/s40854-020-00205-1
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Text-mining technologies have substantially affected financial industries. As the data in every sector of finance have grown immensely, text mining has emerged as an important field of research in the domain of finance. Therefore, reviewing the recent literature on text-mining applications in finance can be useful for identifying areas for further research. This paper focuses on the text-mining literature related to financial forecasting, banking, and corporate finance. It also analyses the existing literature on text mining in financial applications and provides a summary of some recent studies. Finally, the paper briefly discusses various text-mining methods being applied in the financial domain, the challenges faced in these applications, and the future scope of text mining in finance.
引用
收藏
页数:25
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