The in-depth integration of big data technology and red cultural resources promotes the integration of red cultural resources into the integrated construction of the Civic and Political Science curriculum. In this paper, we use information gained to extract the text features of red cultural resources, combine TF*IDF to calculate the weights of feature items, represent the text to the vector space model, put forward the automatic classification algorithm of decision tree red cultural resources text, and build the framework system of red cultural resources text classification. Teaching stage and political appearance are used as independent variables, respectively, to explore the differences in the teaching effect of Civics courses at different stages of universities, secondary schools, and elementary schools as well as among CPC members, members of the League, and the people, and focuses on analyzing the utilization rate of the red cultural resources of Civics course teaching as well as the students’ participation degree. The results show that only 0.0537 students think that the school functionaries are not working correctly, and there exist 0.4308 students who believe that the classroom teaching is not innovative enough. Combining red cultural resources and the integrated teaching of Civic and Political Science courses requires more excavation of red cultural resources and connotations and the formation of characteristic teaching.