Research on the dissemination path of ancient Chinese literature based on discrete regression algorithm in the era of big data

Abstract

As a treasure of Chinese culture, the investigation of the dissemination path of ancient Chinese literature is an important anchor point for inheritance and development. In this paper, we combine ridge regression and quantile regression to perform ridge regression on the sample data of dissemination degree and dissemination path of ancient literature, and then perform quantile regression on the dissemination path variables obtained after screening by ridge regression, and further regression tests are conducted on the variables directly excluded by ridge estimation to finally establish the discrete regression equation of dissemination degree and dissemination path of ancient literature. The coefficients of video dissemination were greater than 0 at all quartiles from 0.1 to 0.9, indicating that video dissemination had a positive effect on dissemination degree at all quartiles. In contrast, the effect of self-publishing on propagation is significant at quantile points greater than 0.4, and the coefficient of sound propagation passes the test of significance level of 0.05 at quantile point 0.3. Based on the analysis of discrete regression, an effective communication model of ancient Chinese literature is established, which lays the foundation for its deeper communication in the era of big data.