A Visual Analysis of Research on Learners' Emotion Perception in China by Using CiteSpace

It is an important issue to effectively perceive learners' emotional state in the field of smart education, which helps to enhance the interaction between teaching groups and stimulate learners' enthusiasm for learning. Taking “emotion perception” as the theme, this paper retrieved 533 relevant core literature from the CNKI (China National Knowledge Infrastructure) database and used econometric methods and visualization software CiteSpace to analyze the number of literature, authors, institutions, and keywords. The results show that the number of literature published on learners' emotion perception has increased year by year in the past 30 years and is in the mature stage of development; The authors and institutions are relatively scattered, and the core research system of emotion perception has not been formed. Building a multimodal perception model using techniques such as expression recognition, posture recognition, and physiological parameter detection is research hotspots in the field of emotion perception. The research trends in this field are to collect and fuse multimodal emotional data, and deeply analyze the change rule of learners' emotions based on deep learning and data mining.