Monitoring the internet media opinion information quickly triggered by the implementation of the “double reduction” policy, and identifying the hot spots, tendencies, communication trends, and characteristics of media opinion are of great significance to government departments to grasp the dynamics of media opinion in time and assist them in decision-making. This paper uses the web crawler to dynamically collect the internet media opinion big data related to the “double reduction” of main media and utilizes text analysis and data mining technologies to dynamically monitor the hot spots, topic tendencies, and communication characteristics of media opinion. Taking the internet media opinion data on the implementation of the “double reduction” policy from January 1, 2021 to November 15, 2021 as the sample, the paper analyzes the media opinion of the implementation of the “double reduction” policy. The high incidence period of media opinion is consistent with the opening of primary and secondary schools, holidays, and the introduction of relevant policies. The topics of internet media opinion are highly targeted and cover a wide range. The media focuses on the implementation measures, new problems, new phenomena, effects, and evaluation of the “double reduction” policy in education. Strong provinces of education, large provinces of education, and difficult provinces of education are the main areas for media public opinion monitoring. The media opinion is in the fermentation stage, and there is no sign of heat reduction. The propagation of media opinion is in line with the theoretical characteristics of information propagation life cycle. This paper only takes the internet media opinion of the main network media as the monitoring object. Whether it is suitable for the media opinion of the whole network media needs to be further tested.

Based on the SBM model including unexpected output, this paper studies the water resource utilization efficiency of 30 provinces in China from 2003 to 2019. The study found that China’s water resource utilization efficiency showed obvious provincial differences. The water resource utilization efficiency of most eastern coastal provinces was relatively high, and that of most central and western inland provinces was not high. There are also significant differences among the three regions of the East, the middle, and the West. The utilization efficiency of water resources in the East is the highest, followed by the middle, and the West is the lowest. The redundancy of input factors, such as labor, capital, and water consumption, is the main reason for the low efficiency of water resource utilization, and the redundancy of wastewater discharge also affects the efficiency of water resource utilization. The clustering results show that the utilization efficiency of water resources in most provinces of China is located in medium efficiency area and low efficiency area, and the efficiency needs to be improved. There are relatively few provinces in high-efficiency areas, highlighting that China’s water resource utilization still faces severe challenges.

With the advent of the crossborder e-commerce (CE) boom, more and more traditional enterprises have transformed into the field of crossborder e-commerce. It has become a new outlet for enterprises in the international trade environment, and at the same time, it has some problems in the utilization of resources and the maximization of benefits. In response to this problem, it is very important to optimize the export operation model of crossborder e-commerce enterprises (CEE). With the development of intelligent algorithms, research on the application of intelligent algorithms to the economic field has gradually been carried out. Its characteristics and advantages are of great significance to the optimization of CEE export operation mode. The purpose of this paper is to study the CEE export operation mode and optimization strategy based on data mining algorithm (DMA). Through the analysis and research of DMA, it can be applied to the optimization of CEE export operation mode to cope with the world trade in the new environment. This paper explains the basic theory of DMA and CEE export operation mode. Its effect is experimentally analyzed, and the relevant theoretical formulas are used to explain. The results show that the comprehensive trade quality index of the CEE export operation mode integrating DMA is higher, and the adaptability is stronger. Compared with the traditional operating model, the difference between the two indices is 3.175 index points. It has guiding significance in terms of CEE export operation mode and optimization strategy.