Comprehensive review of text-mining applications in finance

Aaryan Gupta · Vinya Dengre · Hamza Abubakar Kheruwala · Manan Shah

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Computational and Text Analysis Methods Sentiment Analysis and Opinion Mining Stock Market Forecasting Methods

Abstract

Abstract 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.

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References

2011When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks 1991Efficient Capital Markets: II 1991Efficient Capital Markets: II 2002Investor psychology in capital markets: evidence and policy implications 2019Uncertainty in big data analytics: survey, opportunities, and challenges 2006Tapping the power of text mining 2017A Survey of Text Mining in Social Media: Facebook and Twitter Perspectives 2016Natural Language Processing in Accounting, Auditing and Finance: A Synthesis of the Literature with a Roadmap for Future Research

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