Abstract
Abstract Exploring the evolutionary process of the concept of science and technology in modern Chinese society is conducive to the innovation of the current path of science education popularization and scientific and technological literacy enhancement. In this paper, we construct a sampling selection algorithm using Bayesian and MCMC and then design a parameter derivation model. Assuming the model prior distribution hyperparameters and using the likelihood function to derive the specific form of the posterior probability distribution, an approximate integral calculation is carried out in order to directly derive the parameters to be estimated, and the BVAR-MCMC model is constructed. Using the model to analyze the temporal changes in the evolution of scientific and technological concepts in modern China, it is finally found that the changes in social and technological concepts during the Republican period were even stronger than those in the late Qing period. Influenced by the increasing scale of cross-cultural exchanges due to the gradual opening up of the gateway, cross-cultural open exchanges have the highest impulse value and the longest duration on the evolution of scientific and technological concepts, with the impulse of the Late Qing and the Republic of China phases above 1, and the duration of the positive influence covers the whole time series. The impulse values of the late Qing and the Republic of China are 2.68 and 3.59, respectively, and the education popularization rate, economic development level, the speed of technological life progress, and the degree of civilization and freedom of the social atmosphere have different degrees of influence on the evolution of scientific and technological concepts in the time series of modern history. This study innovates the statistical research method for modern history and conducts a pioneering exploratory study on the evolutionary process of modern social ideas change.
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