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Journal of Scientific Information Research

Keywords

news evaluation, text mining, stock market, semantic association

Abstract

[Purpose/significance]To identify crucial financial news information and tap its potential value related to specific stocks more quickly and accurately, we conduct financial news correlation measurement research in terms of stocks.[Method/process]Natural Language Processing and Machine Learning are used to measure the correlation by text analysis in the word's dimension. Then, the theory of quantifying news is applied to construct a stock-oriented evaluation index system for financial news correlation.[Result/conclusion]This paper realizes a personalized and automatic measurement of news correlation with the index system. Further, the influence of each index is also be analyzed.

First Page

36

Last Page

48

Submission Date

31-Mar-2023

Revision Date

05-May-2023

Published Date

01-Jul-2023

Reference

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Digital Object Identifier (DOI)

10.19809/j.cnki.kjqbyj.2023.03.004

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