Popularization of Science in Colleges and Universities in the New Network Media Environment Based on Artificial Intelligence

By introducing new network media and artificial intelligence technology into the field of science popularization in colleges and universities, this research strives to solve the practical problems of science popularization websites that are large but not distinctive in the current era, and tries to improve the social impact and economic benefits of such science popularization platforms, so as to promote platform innovation and break away from the stereotyped system design form. Through the establishment of a science popularization system for colleges and universities, the mainstream content management can be achieved, and the differentiation management between the main station and the sub station can be completed. The platform design is implemented by Java EE technology, carrying multi-functional module components, completing the componentized configuration of the system, which can be developed sustainably and has good security. The university science popularization system can operate stably in most environments, and the security management measures are strict. It can take multiple means to effectively protect the security of information, and it is simple and easy to implement. It can be seen from the design of simulation experiment that this promotion system, through the design of hybrid recommendation strategy, can_ UserCF and SBBRM_ Based on the advantages of Doc2Vec algorithm, the accuracy and coverage of system recommendations are improved, making it more universal. And the hybrid recommendation results can be compared with the main recall model to prove the efficiency of the system. This paper introduces artificial intelligence technology into the field of science popularization in colleges and universities, so as to realize the system design and improvement based on the new network media environment.