Siamese Graph Convolutional Split-Attention Network with NLP based Social Sentimental Data for enhanced stock price predictions

Siamese Graph Convolutional Split-Attention Network with NLP based Social Sentimental Data for enhanced stock price predictions

Abstract Predicting stock market behavior using sentiment analysis has become increasingly popular, as customer responses on platforms like Twitter can influence market trends. However, most existing sentiment-based models struggle with two major issues: inaccuracy and high complexity. These problem...

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Bibliographic Details
Main Authors: Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni
Format: Article
Language:English
Published: SpringerOpen 2024-10-01
Series:Journal of Big Data
Subjects:
Real time twitter data
Cross domain Swin fusion Transformer (CDSFT)
Circle-Inspired Optimization Algorithm (CIOA)
Siamese Graph Convolutional Split-Attention Network (SGCSAN)
Humboldt Squid Optimization Algorithm (HSOA)
Online Access:https://doi.org/10.1186/s40537-024-01016-2
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https://doi.org/10.1186/s40537-024-01016-2

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