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
: These represent emotions in a geometric space, often using two primary axes: Valence : How positive or negative a feeling is.
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: An Analysis of Feeling
Researchers and psychologists use several established models to categorize and measure feelings:
: Typically lists six basic emotions: anger, disgust, fear, happiness, sadness, and surprise. An "Analysis of Feeling" typically refers to the
The Geneva Emotion Wheel (GEW) is a prominent tool that maps 20 emotion families across these dimensions.
: This identifies a set of "basic" emotions. In the digital age, "feeling analysis" is often
: The level of physical excitation or personal power associated with the feeling.