In recent years, with the rapid development and wide application of the Internet, it has become the main place for the generation and dissemination of public opinion. To grasp the information of network public opinion in a timely and comprehensive way can not only effectively prevent sudden network malignant events but also provide a reference for the scientific and democratic decision-making of government departments. Therefore, in view of the practical application needs, this article studies the emotional characteristics and the evolution of public opinion over time based on the emotional feature words of network public opinion participants. Firstly, the positive and negative emotional lexicon of HowNet emotional dictionary is used, and the commonly used emotional lexicon and expression symbols are added to the lexicon. At the same time, the polarity annotation method of Chinese emotional lexicon ontology is used to construct the emotional lexicon of this article. Secondly, considering other emotional polarity characteristics in the dictionary, an emotional tendency analysis model is proposed. In this article, emotional analysis is applied to the evolution analysis of network public opinion, and the change of network public opinion characteristics with time series is obtained. The simulation results show that the emotional dictionary constructed in this article and the proposed model of emotional orientation analysis can effectively analyze the emotional characteristics of network public opinion participants and apply emotional analysis to the evolution analysis of network public opinion, which can get the change of emotional characteristics of public opinion participants with time series.

In the current teaching of politics, teachers still focus on the cultivation of the basic intelligence of students’ language intelligence, and it is easy to ignore the cultivation of other intelligences that affect the overall development of students. This research mainly discusses the design of curriculum ideological and political teaching platform based on the fusion of multiple data and information in an intelligent environment. This research adopts the MVC architecture, and the web application developed based on the MVC (Model View Controller) architecture pattern is easier to complete the realization of multiple controllers. The front desk ideological and political teaching teacher module includes the login system. In addition, the teacher can view the test status of a specific student and can also pay attention to the total intelligence of all students who have been tested. The process of the student test is to enter the correct account and password to log in to the system and then perform the test. After the test, the test result can be viewed, and the personal information can be maintained at the same time. In addition, the personal login password can be modified. The existence of the database is to ensure that the data is correct and effective. This system uses MySql to design the database, and the name of the database is braintest_db. The data table in relational database is the main object of storing and managing data, and it is also an important task of database design. This system has designed three kinds of user logins, namely, administrator, student, and teacher, and login can be realized according to the account number and password. Among them, teacher’s participation is by inquiring about students’ test situation, paying attention to students’ multiple intelligences, and teaching students in accordance with their aptitude. In addition, the main object of this test is students, and the analysis of multiple intelligences is realized through student tests. Students are vitally physical objects that can be tested and searched for results. In the study, 20% of the students both learn the basic content of the platform and use the forum. This research will help improve students’ literacy in an all-round way.

It is an unavoidable requirement of higher education to thoroughly refine the scientific concept of development and explore the innovative and entrepreneurial education of college students. Wide and effective creative and business literacy training for college students is an important means to reduce the fierce competition for jobs and an effective way to further build an innovative country. The purpose of this paper is to conduct an in-depth study on effective strategies to optimize creative and business literacy training for college students in the context of Internet+. This paper examines how to optimize college students’ creative and business literacy training in the context of Internet+, explains the related concepts and development status of college students’ creative and business literacy training, and discusses the value and practical significance of college students’ creative and business literacy training as well as the current innovation of college students in China. Opportunities, challenges, and problems are encountered in entrepreneurship. Survey experiments were conducted. The results show that more than 83.6% of graduates have some idea about creative and business literacy training, but the satisfaction of college students with the current creative and business literacy training is only 58.2%. Finally, this article suggests five points for optimizing college students.

In the Internet environment, college innovation and entrepreneurship will face more opportunities and challenges. “Internet +” simply means “Internet + traditional industries.” With the development of science and technology, the use of information and Internet platforms enables the integration of the Internet and traditional industries and uses the advantages and characteristics of the Internet to create new development opportunities. University learners are one of the most important contact groups on the Internet. They are generally familiar with the Internet and are good at using Internet channels and Internet thinking to solve problems. Therefore, they are able to grasp opportunities and achieve breakthroughs. Innovation and entrepreneurship education is aimed at cultivating talents with basic entrepreneurial qualities and pioneering personality, and it is an education to cultivate innovative thinking and entrepreneurial ability for the whole society in stages and at different levels. How to effectively use the dividends of Internet entrepreneurship to realize their own transformation and growth is a topic worth studying. Therefore, this paper takes the life cycle of “Internet +” college students’ innovation and entrepreneurship competition as an example, summarizes the achievements and problems of a university in holding the competition, and puts forward countermeasures and suggestions for optimizing and organizing the competition on this basis. Experiments show that the quality of the competition itself, the relevant rules of the competition, the impact of the external environment, and home-school cooperation will have a greater impact on students’ innovation and entrepreneurship performance.

With the increasing development of multimedia teaching, the combination of virtual reality (VR) and video image control has very attractive development prospects in ideological and political teaching, for example, the use of virtual technology in games and so on. However, most virtual reality environments are currently built, and the functional development of artificial intelligence multimedia teaching systems is not comprehensive. An artificial intelligence VR video image control system is constructed for the multimedia teaching system. This article analyzes the development of artificial intelligence multimedia teaching systems and compares the detection performance and efficiency of traditional methods and artificial intelligence multimedia VR ideological and political teaching. Research shows that, in the use of VR to control the images of ideological and political teaching, the average accuracy of these ten video images is 75.68%. This shows that the video image classification and detection algorithm model based on artificial intelligence in this paper can extract deeper and more abstract features to classify the target. The artificial intelligence VR video image control algorithm constructed in this paper can reduce the maximum failure rate by 49.16%, 61.02%, and 66.94%, respectively. Compared with the traditional algorithm, the artificial intelligence VR video image control algorithm constructed in this paper can reduce the storage access delay time of 10 different video images by an average of 15.93%, can obtain about 9.37% performance optimization, and can reduce the video image control time by 7.28% and 10.63%, respectively. For pictures, the artificial intelligence VR video image control system in this article can increase the performance by up to 28.49%.