This is a simple web service used to classify text into its pertaining emotion. It works with languages such as English, Spanish and French. A Research Project by IDEALab. Presented in ASONAM 2015
Traditional classifiers require extracting high dimensional feature representations, which become computationally expensive to process and can misrepresent or deteriorate the accuracy of a classifier. By utilizing a more representative list of extracted patterns, we can improve the precision and recall of a classification task. In this paper, we propose an unsupervised graph-based approach for bootstrapping Twitter-specific emotion-bearing patterns. Due to its novel bootstrapping process, the full system is also adaptable to different domains and classification problems. Furthermore, we explore how emotion-bearing patterns can help boost an emotion classification task. The experimented results demonstrate that the extracted patterns are effective in identifying emotions for English, Spanish and French Twitter streams.
In progress 🚧
- Convert the service into API
- Beautification
- Integration with other services
- Fork repository
- Submit Pull Request
For questions please email: ✉️ [email protected]