A comprehensive review on sentiment analysis of social/web media big data for stock market prediction
It is generally known that public opinion and stock market dynamics are inextricably linked. With the growth of social and web-based media, online platforms have emerged as a key gauge of public mood. This digital environment produces a lot of data quickly. This extensive dataset's analysis off...
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Published in: | International journal of system assurance engineering and management Vol. 15; no. 6; pp. 2011 - 2018 |
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Main Authors: | , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
New Delhi
Springer India
2024
Springer Nature B.V |
Subjects: | |
Online Access: | Get full text |
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Summary: | It is generally known that public opinion and stock market dynamics are inextricably linked. With the growth of social and web-based media, online platforms have emerged as a key gauge of public mood. This digital environment produces a lot of data quickly. This extensive dataset's analysis offers priceless insights into the general public's perception, which in turn might influence market performance. The vast array of approaches for efficiently processing the sizable amount of data originating from social and web-based media are reviewed in detail in this study. Additionally, it looks at studies exploring the integration of big data analytics and sentiment insights for more accurate market predictions, as well as studies studying the prediction of stock market trends using sentiment analysis. |
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ISSN: | 0975-6809 0976-4348 |
DOI: | 10.1007/s13198-023-02214-6 |