hybrid approaches in emotion recognition are essentially a combination of knowledge-based techniques and statistical methods, which exploit complementary characteristics from both techniques. some of the works that have applied an ensemble of knowledge-driven linguistic elements and statistical methods include sentic computing and ifeel, both of which have adopted the concept-level knowledge-based resource senticnet. the role of such knowledge-based resources in the implementation of hybrid approaches is highly important in the emotion classification process. since hybrid techniques gain from the benefits offered by both knowledge-based and statistical approaches, they tend to have better classification performance as opposed to employing knowledge-based or statistical methods independently. a downside of using hybrid techniques however, is the computational complexity during the classification process.