Beyond Sentiment: The Manifold of Human Emotions

TL;DR

This paper introduces a continuous manifold model for human emotions in text, extending sentiment analysis to capture a richer, multidimensional emotional spectrum and improving prediction accuracy.

Contribution

It presents a novel continuous manifold approach for modeling human emotions, surpassing previous finite-set sentiment models and aligning with psychological observations.

Findings

Significant improvement over baseline models

Visualization of domain-specific positive sentiments

Alignment with psychological emotion theories

Abstract

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. Besides obtaining significant improvements over a baseline without manifold, we are also able to visualize different notions of positive sentiment in different domains.