Under the background of the development of the network information age, the current Internet industry has obtained more development opportunities, but it has also brought corresponding challenges in the process of wide application. In the development and construction of modernization, society pays more attention to the supervision and determination of the characteristics of online public opinion. From the perspective of the current characteristics of network public opinion, because social information is more extensive and involves many fields, network public opinion has a high degree of complexity and diffusion. Therefore, it is necessary to strengthen the analysis and application of relevant data mining systems in order to achieve efficient management of network public opinion. The key to the disadvantage of the traditional excavation of public opinion communication characteristics lies in the lag of the excavation process, and it is difficult to deal with malignant public opinion in a timely and effective manner. Therefore, in order to truly solve the lagging problem of public opinion data dissemination feature mining technology, it is necessary to strengthen the application of artificial intelligence technology in it.

Terms and Conditions are always encountered when using social media applications to determine which data can be accessed and what cannot.  However, there are shortcomings in their implementation and communication, often causing users to be unwilling to read them. Therefore, this study aimed to analyze the effectiveness of implementing partial consent in Terms and Conditions concerning user Data Awareness and Data Security in social media. This Paper administered a questionnaire, distributed with a form, to students who use social media to understand their opinions regarding the partial consent concept. This paper analyzed the data using descriptive statistical methods. The results show a positive response from respondents towards implementing the partial consent concept, the users feel the terms and conditions are more effective in increasing user data awareness and security.

To address gaps in practical skills among Public Health and Preventive Medicine graduates, an ‘open collaborative practice teaching model’ integrating medicine, teaching, and research was introduced. A cross-sectional study surveyed 312 Preventive Medicine undergraduates at a Yunnan medical university from 2020 to 2023, utilizing satisfaction scores and analyses (cluster, factor, SWOT) to assess the impact of the reform. Satisfaction scores from baseline, mid-term, and end-term assessments showed minor variations (4.30, 4.29, 4.36), with dissatisfaction primarily related to teaching content and methods. Key influences on satisfaction included teaching content, methods, and effectiveness. The SWOT analysis highlighted the importance of continuously updating teaching strategies to meet changing student expectations. This study suggests that the model has the potential for wider use in enhancing public health education, particularly in regions facing similar challenges.