Multi-Modal Opinion Integration for Financial Sentiment Analysis using Cross-Modal Attention

This article describes a research paper on financial sentiment analysis. The core of the research involves integrating multiple data modalities (e.g., text, numerical data) to improve the accuracy of sentiment prediction. The use of cross-modal attention is a key technical aspect, allowing the model to learn relationships between different data types. The focus is on improving the performance of sentiment analysis in the financial domain.

• •Focuses on financial sentiment analysis.
• •Employs multi-modal data integration.
• •Utilizes cross-modal attention mechanisms.
• •Aims to improve sentiment prediction accuracy.