Research Challenges Plutchik's Wheel of Emotion Through Semantic Network Analysis
A study published on arXiv (ID: 2602.06430v2) critically examines the validity of Plutchik's wheel of emotion, a popular model used in natural language processing for sentiment analysis. Researchers constructed semantic networks based on similarity and association data collected from ordered pairs of emotion words. Community detection methods were applied to analyze the structural properties of these networks. The investigation revealed that the network structures largely resembled the circular organization proposed by Plutchik's model. This research addresses a gap in the field where the wheel's validity had not been sufficiently tested despite its widespread application. The work contributes to computational linguistics by empirically evaluating foundational emotion models through network science approaches.
Key facts
- Study examines validity of Plutchik's wheel of emotion
- Uses semantic networks of emotion words
- Analyzes similarity and association data from ordered word pairs
- Applies community detection methods to network structures
- Finds network structures largely similar to Plutchik's model
- Addresses insufficient prior examination of the model's validity
- Published on arXiv with ID 2602.06430v2
- Announcement type: replace-cross
Entities
Institutions
- arXiv