New Media Art Design in Chinese Cultural Communication Based on Logistic Regression Model

Abstract

The purpose of exploring the application of new media art design in Chinese cultural communication is to promote a wider dissemination of Chinese culture through new media. In this paper, starting from the logistic regression algorithm, the loss function is optimized by using maximum likelihood estimation, and a sparse logistic regression model is constructed by introducing sparse prior factors. Ten-fold cross-validation performance evaluation and example analysis are conducted for the model. From the performance evaluation, the average check accuracy rate of the sparse logistic regression model is 92.27% and the average check completeness rate is 7.88%. From the analysis of cultural communication applications, the best application carrier for cultural communication is historical digital video resources, which accounts for 42.7%, and the type of communication is style-based video, which has increased by 18.13 percentage points from 2017 to 2021. This shows that the use of logistic regression model can effectively analyze the application of new media art and design in Chinese cultural communication, and also provides a new path for Chinese cultural communication.