Semantically Enriching Investor Micro-blogs for Opinion-Aware Emotion Analysis: A Practical Approach
Researchers have developed a method to semantically enrich investor micro-blogs for more nuanced emotion analysis in financial NLP. This approach augments the StockEmotions dataset with structured opinion graphs, providing deeper semantic understanding beyond basic sentiment and emotion labels. By using a declarative LLM pipeline and Graph Neural Networks (GNNs), the study shows that incorporating these opinion semantics significantly improves classification performance across various emotional spectrums. AI
IMPACT Enhances financial NLP by providing deeper insights into investor sentiment and the reasoning behind it.