Research on Discourse Reconstruction Effect of Animated Film Cross-Cultural Communication Based on Machine Learning

Abstract

Animated films are an important carrier of cultural dissemination, a way of conveying national culture and displaying regional culture in film and television, and an important medium for constructing national image and cultural form in the process of cross-cultural dissemination. The special film language expression of emotion in animated films also highlights its unique charm, status, and cultural communication role in the field of communication and at the same time reflects the unique value of the flash point in the ever-changing modern society. This paper starts with the related concepts of machine learning models, analyzes machine learning characteristics and model quality factors, and builds a model evaluation index system based on this and then proposes machine learning model evaluation implementation and index data processing methods. In building the corresponding evaluation experiment, the training model and animation film sentiment classification analysis need big data animation film culture data; the existing open source experimental data is very small and not suitable for the experiment of this paper. The principle of support vector machine is mainly introduced. And an improved machine learning model for animated film cultural sentiment classification is built. Experiments show that the performance of each index of the improved machine learning model is better than that of the support vector machine classifier.