基于网络搜索数据的社会消费品预测研究

With the rapid development of Internet, network search data has gradually become an important data source of economic prediction. Based on the network search data, this paper forecasts the total retail sales of social consumer goods. On the basis of selecting the appropriate network search data and traditional government data by Spearman correlation coefficient, through PCA dimensionality reduction processing, the network search data and traditional government data are used as the input variables of neural Research on prediction of total retail sales of social consumer goods based on network search datanetwork model to predict the total retail sales of social consumer goods in China. The results show that the model combining government data and network search data has the best prediction effect compared with the model using government data and network search data alone. The analysis of the model results aims to provide some reference for government departments to formulate policies to stimulate domestic demand.