The traditional mental health education model has made it difficult to cope with the increasingly serious psychological problems of college students. In this paper, under the perspective of “Internet+”, based on the social network of college students, we constructed a propagation dynamics model of depression in colleges and universities and utilized the heterogeneous mean field to detect the propagation status of students’ depression. After calculating the comprehensive centrality degree of students with depression, the community mining of peer psychological adjustment is completed. The C-P similarity of students under the mental health perspective was defined by the ordering of the comprehensive centrality degree and the friend recommendation results were obtained by the distance measure of similarity. In the network of students without depressed mood, after a period of oscillation initially, the end state can be basically reached within 1000 steps, and the infected nodes reach 1000. When the depressed mood factor is small, such as S=0.02 and S=0.04, it has been able to prevent the transformation of depressed mood to the state of all 0, and the proportion occupied by positive and negative moods in the network is basically stable. Internet technology effectively improves the problem of identifying students with psychological abnormalities and implementing targeted mental health education.