A Study on the Construction of Knowledge Mapping for Teaching English Politeness in Global Cultural Communication in the Information Age

In this paper, based on the characteristics of teaching English polite phrases, the acquired research data are subjected to the segmentation operation, and a graph convolutional neural network is used to iteratively train them, finally completing the modeling of the knowledge graph of English polite phrases and determining the parameters of the model. The constructed knowledge graph is ready to be introduced into the English polite language teaching activities, and a model for teaching English polite language has been designed based on it. Simulation experiments and independent sample t-tests are used to validate and analyze the knowledge graph model and the teaching model, respectively. Upon analysis, it was found that the model in this paper could quickly and accurately identify the number of times the English verbs of polite phrases appeared, which was reflected in the fact that Promise appeared five times and Praise appeared four times. After the teaching intervention, the English test scores of students in Group E (Mean: 15.994) were significantly higher than those of Group C (Mean: 12.152), and the difference between the scores of the two groups was statistically significant (t=6.811, P=0.002