Beyond Sentiment Classification: A Generative Framework for Emotion Intensity Evaluation in Text
Measuring how intensely emotional text is, not just what emotion it shows
Researchers created a new way to analyze emotions in text by measuring their strength on a scale from 0 to 100, rather than sorting text into fixed categories like "positive" or "negative." This approach outperformed traditional emotion classification and unexpectedly transferred well to related concepts like sentiment and arousal.
Financial markets move on emotion as much as data. A trader's brief worry about inflation differs radically from panic selling — but traditional sentiment tools treat both the same way. By measuring emotional intensity rather than just labeling sentiment, analysts can better gauge market psychology and make sharper predictions about how people will actually respond to news.