In the digital age, "feeling analysis" is often performed by AI using Natural Language Processing (NLP) to process large datasets like social media or customer reviews:
: These represent emotions in a geometric space, often using two primary axes: Valence : How positive or negative a feeling is.
An "Analysis of Feeling" typically refers to the systematic study of human emotions, often through the lens of or Emotion Detection in data science . While sentiment analysis focuses on the broad polarity of text (positive, negative, or neutral), emotion analysis delves deeper into specific states like joy, fear, anger, or sadness. Core Approaches to Analyzing Feeling An Analysis of Feeling
: This identifies a set of "basic" emotions.
Researchers and psychologists use several established models to categorize and measure feelings: In the digital age, "feeling analysis" is often
The Geneva Emotion Wheel (GEW) is a prominent tool that maps 20 emotion families across these dimensions.
: Arranges 8 primary emotions (and their opposites) on a color-coded wheel to show how they blend. Computational Techniques Core Approaches to Analyzing Feeling : This identifies
: The level of physical excitation or personal power associated with the feeling.