PyPlutchik

PyPlutchik visualizes emotional content in textual corpora using Robert Plutchik's emotion model to represent eight primary emotions, three intensity levels, and dyadic relationships.

Key Features:

• Plutchik's Wheel Visualization: Represents emotions with a flower-like structure where each petal corresponds to one of the eight primary emotions and petal size reflects emotion frequency or intensity.
• Intensity Representation: Distinguishes three degrees of emotional intensity for each primary emotion.
• Dyadic Relationships: Illustrates primary, secondary, tertiary, and opposite dyads to capture combinations and semantic oppositions among emotions.
• Comparative Analysis: Enables visual comparison of emotional fingerprints across different corpora.

Scientific Applications:

• Emotion Detection: Provides visual summaries of detected emotions in textual corpora.
• Sentiment Analysis: Supports analysis of sentiment trends in social media and other textual datasets.
• Psychological Research: Aids studies of emotional expression in communication, literature, and digital interactions.

Methodology:

Implemented as a Python module that maps detected emotion frequencies and intensities onto Plutchik's wheel by scaling petal sizes, encodes three intensity degrees, and represents primary, secondary, tertiary, and opposite dyads for comparative visualization across corpora.