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
Digital Object Identifier (DOI)
10.19809/j.cnki.kjqbyj.2023.03.004
Recommended Citation
SHI, Jing; ZHANG, Bin; and CHEN, Ye
(2023)
"Stock-Oriented Measurement of Financial News Correlation:Based on Theory of Quantifying News Value,"
Scientific Information Research: Vol. 5:
Iss.
3, Article 4.
DOI: 10.19809/j.cnki.kjqbyj.2023.03.004
Available at:
https://eng.kjqbyj.com/journal/vol5/iss3/4
Reference
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