Evaluation of emotion classification schemes in social media text: an annotation-based approach
The AHP evaluation result shows that Ekman's scheme had the highest score. The multi-dimensional scaling (MDS) analysis shows that Ekman, Plutchik, and the Seven Emotions are relatively similar. We analyzed Ekman's six basic emotions in relation to the emotion categories of the other schemes. The correspondence analysis shows that the Seven Emotions' joy aligns with Ekman's happiness, love demonstrates a significant correlation with happiness, but desire is not significantly correlated with any emotion. Compared to Ekman, Plutchik has two more positive emotions: trust and anticipation. Trust is somewhat associated with happiness, but anticipation is weakly associated with happiness. Each emotion of Ekman's corresponds to several similar emotions in GoEmotions. However, some emotions in GoEmotions are not clearly related to Ekman's, such as approval, love, pride, amusement, etc. CONCLUSION: Ekman's scheme performs best under the evaluation framework. However, it lacks sufficient positive emotion categories for the corpus.
Authors
- Qiang Tang (ORCID: https://orcid.org/0000-0002-6153-4255)
- Fa Zhang (ORCID: https://orcid.org/0000-0002-2081-9369)
- Yan Tian
- Jian Chen (ORCID: https://orcid.org/0000-0003-1775-0134)
Institutions
- Guangdong Polytechnic of Science and Technology (CN)
- Zhuhai Institute of Advanced Technology (CN)
Publication Details
- Journal
- BMC Psychology
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1186/s40359-024-02008-w
- Citations
- 14
- Primary Topic
- Sentiment Analysis and Opinion Mining
- Type
- article
- Field-Weighted Citation Impact
- 4.86
Funders
- National Natural Science Foundation of China