Publication Type

Journal Article

Publication Date

9-2016

Abstract

In finance and accounting, relative to quantitative methods traditionally used, textual analysis becomes popular recently despite of its substantially less precise manner. In an overview of the literature, we describe various methods used in textual analysis, especially machine learning. By comparing their classification performance, we find that neural network outperforms many other machine learning techniques in classifying news category. Moreover, we highlight that there are many challenges left for future development of textual analysis, such as identifying multiple objects within one single document.

Keywords

Machine learning, Textual analysis, Finance, Accounting, Media news, Sentiment, Information

Discipline

Finance | Finance and Financial Management

Research Areas

Finance

Publication

The Journal of Finance and Data Science

Volume

2

Issue

3

First Page

153

Last Page

170

Identifier

10.1016/j.jfds.2017.02.001

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

https://doi.org/10.1016/j.jfds.2017.02.001

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