Optimal Information Dissemination Model for College Students' Network Interactive Platform Assisted by Big Data Repeated Mining Algorithm

Firstly, the college students' network interaction platform of the student's preferred course plan model is constructed, and the big data analysis method is used to carry out the information fusion and optimal access design of the student's course selection resource database, combined with the adaptive equilibrium game and grey correlation analysis. A parallel algorithm for sentiment analysis of network information is proposed. According to the characteristics of the network information itself, using the MapReduce model, the three main steps of the sentiment analysis task are parallelized and improved, and a sentiment-based dictionary is designed. The Internet education communication model composed of “five elements”.