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Publication detail
JANKOVÁ, Z.
Original Title
Critical review of text mining and sentiment analysis for stock market prediction
Type
journal article in Web of Science
Language
English
Original Abstract
The paper is aimed at a critical review of the literature dealing with text mining and sentiment analysis for stock market prediction. The aim of this work is to create a critical review of the literature, especially with regard to the latest findings of research articles in the selected topic strictly focused on stock markets represented by stock indices or stock titles. This requires examining and critically analyzing the methods used in the analysis of sentiment from textual data, with special regard to the possibility of generalization and transferability of research results. For this reason, an analytical approach is also used in working with the literature and a critical approach in its organization, especially for completeness, coherence, and consistency. Based on the selected criteria, 260 articles corresponding to the subject area are selected from the world databases of Web of Science and Scopus. These studies are graphically captured through bibliometric analysis. Subsequently, the selection of articles was narrowed to 49. The outputs are synthesized and the main findings and limits of the current state of research are highlighted with possible future directions of subsequent research.
Keywords
bibliometric analysis; financial market; literature review; sentiment analysis; stock market; text mining
Authors
Released
5. 4. 2023
Publisher
Vilnius Gediminas Technical University
Location
Vilnius, Lithuania
ISBN
2029-4433
Periodical
Journal of Business Economics and Management
Year of study
24
Number
1
State
Republic of Lithuania
Pages from
Pages to
22
Pages count
URL
https://journals.vilniustech.lt/index.php/JBEM/article/view/18805
Full text in the Digital Library
http://hdl.handle.net/11012/209505
BibTex
@article{BUT183245, author="Zuzana {Janková}", title="Critical review of text mining and sentiment analysis for stock market prediction", journal="Journal of Business Economics and Management", year="2023", volume="24", number="1", pages="1--22", doi="10.3846/jbem.2023.18805", issn="2029-4433", url="https://journals.vilniustech.lt/index.php/JBEM/article/view/18805" }