Classification of financial news articles using machine learning algorithms

Title

Classification of financial news articles using machine learning algorithms

Creator

Saxena A.; Banik A.; Saswat C.; Joan Jose M.; Bhagat V.

Description

The opinion helps in determining the direction of the stock market. Information hidden in news articles is an information treasure which needs to be extracted. The present study is conducted to explore the application of text mining in binning the financial articles according to the opinion expressed inside them. It is discovered that using the tri-n-gram feature extraction process in conjugation with Support Vector machines increases the reliability and precision of the binning process. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.

Source

Lecture Notes in Networks and Systems, Vol-132, pp. 193-199.

Date

2021-01-01

Publisher

Springer

Subject

Classifications; n-grams; Stock market; Support vector machine; Text mining

Coverage

Saxena A., CHRIST (Deemed to be University), Bengaluru, India; Banik A., CHRIST (Deemed to be University), Bengaluru, India; Saswat C., CHRIST (Deemed to be University), Bengaluru, India; Joan Jose M., CHRIST (Deemed to be University), Bengaluru, India; Bhagat V., CHRIST (Deemed to be University), Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 23673370

Format

Online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1007/978-981-15-5309-7_20

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090375590&doi=10.1007%2f978-981-15-5309-7_20&partnerID=40&md5=547939bc37d8157d9d15e0a7debf0c17