The Manifold of Human Emotions
This work addresses the need for more nuanced emotion analysis in text, though it appears incremental as it builds on existing sentiment analysis concepts.
The paper tackles the problem of representing a richer set of human emotions beyond binary sentiment by proposing a continuous manifold model, and it explores this model's alignment with psychology and predictive performance.
Sentiment analysis predicts the presence of positive or negative emotions in a text document. In this paper, we consider higher dimensional extensions of the sentiment concept, which represent a richer set of human emotions. Our approach goes beyond previous work in that our model contains a continuous manifold rather than a finite set of human emotions. We investigate the resulting model, compare it to psychological observations, and explore its predictive capabilities.